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Design With Opamps

Op Amps for Everyone
by Ron Mancini

The operational amplifier (“op amp”) is the most versatile and widely used type of analog IC, used in audio and voltage amplifiers, signal conditioners, signal converters, oscillators, and analog computing systems. Almost every electronic device uses at least one op amp. This book is Texas Instruments’ complete professional-level tutorial and reference to operational amplifier theory and applications. Among the topics covered are basic op amp physics (including reviews of current and voltage division, Thevenin’s theorem, and transistor models), idealized op amp operation and configuration, feedback theory and methods, single and dual supply operation, understanding op amp parameters, minimizing noise in op amp circuits, and practical applications such as instrumentation amplifiers, signal conditioning, oscillators, active filters, load and level conversions, and analog computing. There is also extensive coverage of circuit construction techniques, including circuit board design, grounding, input and output isolation, using decoupling capacitors, and frequency characteristics of passive components. The material in this book is applicable to all op amp ICs from all manufacturers, not just TI. Unlike textbook treatments of op amp theory that tend to focus on idealized op amp models and configuration, this title uses idealized models only when necessary to explain op amp theory. The bulk of this book is on real-world op amps and their applications; considerations such as thermal effects, circuit noise, circuit buffering, selection of appropriate op amps for a given application, and unexpected effects in passive components are all discussed in detail.

*Published in conjunction with Texas Instruments
*A single volume, professional-level guide to op amp theory and applications
*Covers circuit board layout techniques for manufacturing op amp circuits.


Op Amps for Everyone
by Bruce Carter

The operational amplifier (“op amp”) is the most versatile and widely used type of analog IC, used in audio and voltage amplifiers, signal conditioners, signal converters, oscillators, and analog computing systems. Almost every electronic device uses at least one op amp. This book is Texas Instruments’ complete professional-level tutorial and reference to operational amplifier theory and applications. Among the topics covered are basic op amp physics (including reviews of current and voltage division, Thevenin’s theorem, and transistor models), idealized op amp operation and configuration, feedback theory and methods, single and dual supply operation, understanding op amp parameters, minimizing noise in op amp circuits, and practical applications such as instrumentation amplifiers, signal conditioning, oscillators, active filters, load and level conversions, and analog computing. There is also extensive coverage of circuit construction techniques, including circuit board design, grounding, input and output isolation, using decoupling capacitors, and frequency characteristics of passive components. The material in this book is applicable to all op amp ICs from all manufacturers, not just TI. Unlike textbook treatments of op amp theory that tend to focus on idealized op amp models and configuration, this title uses idealized models only when necessary to explain op amp theory. The bulk of this book is on real-world op amps and their applications; considerations such as thermal effects, circuit noise, circuit buffering, selection of appropriate op amps for a given application, and unexpected effects in passive components are all discussed in detail.

*Published in conjunction with Texas Instruments
*A single volume, professional-level guide to op amp theory and applications
*Covers circuit board layout techniques for manufacturing op amp circuits.


Op Amps: Design, Application, and Troubleshooting
by David Terrell

OP Amps deliberately straddles that imaginary line between the technician and engineering worlds. Topics are carefully addressed on three levels: operational overview, numerical analysis, and design procedures. Troubleshooting techniques are presented that rely on the application of fundamental electronics principles. Systematic methods are shown that can be used to diagnose defects in many kinds of circuits that employ operational amplifiers.

One of the book’s greatest strengths is the easy-to-read conversational writing style. The author speaks directly to the student in a manner that encourages learning. This book explains the technical details of operational amplifier circuits in clear and understandable language without sacrificing technical depth.

  • Easy-to-read conversational style communicates procedures an technical details in simple language
  • Three levels of technical material: operational overview, manericall analysis, and design procedures
  • Mathematics limited to algebraic manipulation

Op Amp Applications Handbook
by Walt Jung

In the past several years, many advances have been made in operational amplifiers and the latest op amps have powerful new features, making them more suitable for use in many products requiring weak signal amplification, such as medical devices, communications technology, optical networks, and sensor interfacing. Walt Jung, analog design guru and author of the classic IC OP-Amp Cookbook (which has gone into three editions since 1974), has now written what may well be the ultimate op amp reference book. As Jung says, “This book is a compendium of everything that can currently be done with op amps.” This book is brimming with up-to-date application circuits, handy design tips, historical perspectives, and in-depth coverage of the latest techniques to simplify op amp circuit designs and improve their performance.

There is a need for engineers to keep up with the many changes taking place in the new op amps coming onto the market, and to learn how to make use of the new features in the latest applications such as communications, sensor interfacing, manufacturing control systems, etc.. This book contains the answers and solutions to most of the problems that occur when using op amps in many different types of designs, by a very reputable and well-known author. Anything an engineer will want to know about designing with op amps can be found in this book.

*Seven major sections packed with technical information

*Anything an engineer will want to know about designing with op amps can be found in this book

*This practical reference will be in great demand, as op amps is considered a difficult area in electronics design and engineers are always looking for help with it


Design of CMOS Operational Amplifiers
by Rasoul Dehghani

CMOS operational amplifiers (Op Amps) are one of the most important building blocks in many of todays integrated circuits. This cutting-edge volume provides you with an analytical method for designing CMOS Op Amp circuits, placing emphasis on the practical aspects of the design process. This unique book takes an in-depth look at CMOS differential amplifiers, explaining how they are the main part of all Op Amps. The book presents important details and a design method for the different architectures of single ended Op Amps. You find complete chapters dedicated to the critical issues of CMOS output stages, fully differential Op Amps, and CMOS reference generators. This comprehensive book also includes an introduction to CMOS technology and the basics of the physical aspects of MOS transistors, providing you with the foundation needed to fully master the material.

Analog Circuit Design
by Johan Huijsing, Rudy J. van de Plassche, Willy M.C. Sansen

Many interesting design trends are shown by the six papers on operational amplifiers (Op Amps). Firstly. there is the line of stand-alone Op Amps using a bipolar IC technology which combines high-frequency and high voltage. This line is represented in papers by Bill Gross and Derek Bowers. Bill Gross shows an improved high-frequency compensation technique of a high quality three stage Op Amp. Derek Bowers improves the gain and frequency behaviour of the stages of a two-stage Op Amp. Both papers also present trends in current-mode feedback Op Amps. Low-voltage bipolar Op Amp design is presented by leroen Fonderie. He shows how multipath nested Miller compensation can be applied to turn rail-to-rail input and output stages into high quality low-voltage Op Amps. Two papers on CMOS Op Amps by Michael Steyaert and Klaas Bult show how high speed and high gain VLSI building blocks can be realised. Without departing from a single-stage OT A structure with a folded cascode output, a thorough high frequency design technique and a gain-boosting technique contributed to the high-speed and the high-gain achieved with these Op Amps. . Finally. Rinaldo Castello shows us how to provide output power with CMOS buffer amplifiers. The combination of class A and AB stages in a multipath nested Miller structure provides the required linearity and bandwidth.

Design Criteria for Low Distortion in Feedback Opamp Circuits
by Bjørnar Hernes, Trond Sæther

Broadband opamps for multi-channel communication systems have strong demands on linearity performance. When these opamps are integrated in deep sub-micron CMOS technologies, the signal-swing has to occupy a large part of the rather low supply voltage to maintain the signal-to-noise-ratio. To obtain opamps with low distortion it is necessary to do a thorough analysis of the nonlinear behaviour of such circuits and this is the main subject of Design Criteria for Low Distortion in Feedback Opamp Circuits.

The biasing of each transistor in the circuit is a major issue and is addressed in this work. It is important to bias the transistor such that the distortion is low and stable in the entire range of its terminal voltages. This will ensure high linearity and robustness against variations in circuit conditions such as power supply voltage, bias current and process variations.

Design Criteria for Low Distortion in Feedback Opamp Circuits is written for .


Design of Low-Voltage CMOS Switched-Opamp Switched-Capacitor Systems
by Vincent S.L. Cheung, Howard Cam H. Luong

Demand for low-power low-voltage integrated circuits (ICs) has rapidly grown due to the increasing importance of portable equipment in all market segments including telecommunications, computers, and consumer electronics. The need for low-voltage ICs is further motivated by CMOS technology scaling that requires low supply voltages for device reliability. On the other hand, switched-capacitor (SC) circuits, which have been well known for high accuracy and low distortion, have also become increasingly attractive for low-voltage, low-power, and even high-frequency applications. Switched-opamp (SO) technique has been proposed to enable SC circuits to operate with a single 1-V supply in standard CMOS processes without any clock voltage multiplier or low-threshold devices. However, the existing SO technique requires the opamps to turn off after their integrating phases and thus is not suitable for most of the switched-capacitor systems.

In Design of Low-Voltage CMOS Switched-Opamp Switched-Capacitor Systems, the emphasis is put on the design and development of advanced switched-opamp architectures and techniques for low-voltage low-power switched-capacitor (SC) systems. Specifically, the book presents a novel multi-phase switched-opamp technique together with new system architectures that are critical in improving significantly the performance of switched-capacitor systems at low supply voltages:
*A generic fast-settling double-sampling SC biquadratic filter architecture is proposed to achieve high-speed operation for SC circuits.
*A low-voltage double-sampling (DS) finite-gain-compensation (FGC) technique is employed to realize high-resolution SD modulator using only low-DC-gain opamps to maximize the speed and to reduce power dissipation.
*A family of novel power-efficient SC filters and SD modulators are built based on using only half-delay SC integrators.
*Single-opamp-based SC systems are designed for ultra-low-power applications. In addition, on the circuit level, a fast-switching methodology is proposed for the design of the switchable opamps to achieve switching frequency up to 50 MHz at 1V, which is improved by about ten times compared to the prior arts.

Finally, detailed design considerations, architecture choices, and circuit implementation of five chip prototypes are presented to illustrate potential applications of the proposed multi-phase switched-opamp technique to tackle with and to achieve different stringent design corners such as high-speed, high-integration-level and ultra-low-power consumption at supply voltages of 1V or lower in standard CMOS processes.


Operational Amplifiers
by Johan Huijsing

Operational Amplifiers – Theory and Design is the first book to present a systematic circuit design of operational amplifiers. Containing state-of-the-art material as well as the essentials, the book is written to appeal to both the experienced practitioner and the less initiated circuit designer. It is shown that the topology of all operational amplifiers can be divided into nine main overall configurations. These configurations range from one gain stage up to four or more gain stages. Many famous designs are evaluated in depth.
High-frequency compensation techniques are presented for all nine configurations. Special emphasis is placed on low-power low-voltage architectures with rail-to-rail input and output ranges.
Operational Amplifiers – Theory and Design also develops on the theme of the design of fully differential operational amplifiers and operational floating amplifiers. In addition, the characterization of operational amplifiers by macromodels and error matrices is presented, together with measurement techniques for their parameters.
Carefully structured and enriched by numerous figures, problems and simulation exercises the book is ideal for the purposes of self-study and self-evaluation.

The Arts of VLSI Opamp Circuit Design – A Structural Approach Based on Symmetry
by Hongjiang Song

This text is developed from the notes of a VLSI circuit design class (EEE598) the author offered in Engineering School at Arizona State University. The materials cover the structural design approaches of VLSI operational amplifier circuits based on the symmetry principle, symmetry circuit structures, prototype circuits, and symmetry scaling/transformation techniques.

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Electric Universe

Electric Universe
by David Bodanis

David Bodanis, bestselling author of E=mc2, weaves tales of romance, divine inspiration, and fraud through an account of the invisible force that permeates our universeelectricity—and introduces us to the virtuoso scientists who plumbed its secrets.

For centuries, electricity was seen as little more than a curious property of certain substances that sparked when rubbed. Then, in the 1790s, Alessandro Volta began the scientific investigation that ignited an explosion of knowledge and invention. The force that once seemed inconsequential was revealed to be responsible for everything from the structure of the atom to the functioning of our brains. In harnessing its power, we have created a world of wonders—complete with roller coasters and radar, computer networks and psychopharmaceuticals.

In Electric Universe, the great discoverers come to life in all their brilliance and idiosyncrasy, including the visionary Michael Faraday, who struggled against the prejudices of the British class system, and Samuel Morse, a painter who, before inventing the telegraph, ran for mayor of New York City on a platform of persecuting Catholics. Here too is Alan Turing, whose dream of a marvelous thinking machine—what we know as the computer—was met with indifference, and who ended his life in despair after British authorities forced him to undergo experimental treatments to “cure” his homosexuality.

From the frigid waters of the Atlantic to the streets of Hamburg during a World War II firestorm to the interior of the human body, Electric Universe is a mesmerizing journey of discovery.


A Beginner’s View of Our Electric Universe
by Tom Findlay

Most people just accept that our universe is ruled by gravity; an assumption that is wrong. Evidence instead shows that the force responsible for all the objects and events we observe throughout the universe is the electric force that enables current flow and therefore magnetic fields to exist. If we consider that the electric force is fundamentally one thousand, billion, billion, billion, billion times more powerful than gravity and that the universe consists of 99.99{0ecf78de3233195f9d82930a9ee743635b7624591304904366f348b1037c0f80} plasma; charged matter through which electric currents flow, then you have good reason to open your mind and reading what this book has to say.

Thunderbolts of the Gods
by David Talbott, Wallace Thornhill, Mel Acheson

A radical reinterpretation of human history and the evolution of the solar system based on the witness of ancient catastrophe caused by major electrical activity between the planet gods. Includes DVD inside back cover.

Science Set Free
by Rupert Sheldrake

The bestselling author of Dogs That Know When Their Owners Are Coming Home offers an intriguing new assessment of modern day science that will radically change the way we view what is possible.

In Science Set Free (originally published to acclaim in the UK as The Science Delusion), Dr. Rupert Sheldrake, one of the world’s most innovative scientists, shows the ways in which science is being constricted by assumptions that have, over the years, hardened into dogmas. Such dogmas are not only limiting, but dangerous for the future of humanity.

According to these principles, all of reality is material or physical; the world is a machine, made up of inanimate matter; nature is purposeless; consciousness is nothing but the physical activity of the brain; free will is an illusion; God exists only as an idea in human minds, imprisoned within our skulls.

But should science be a belief-system, or a method of enquiry? Sheldrake shows that the materialist ideology is moribund; under its sway, increasingly expensive research is reaping diminishing returns while societies around the world are paying the price.

In the skeptical spirit of true science, Sheldrake turns the ten fundamental dogmas of materialism into exciting questions, and shows how all of them open up startling new possibilities for discovery.

Science Set Free will radically change your view of what is real and what is possible.

From the Hardcover edition.


Physics of the Plasma Universe
by Anthony L. Peratt

Today many scientists recognize plasma as the key element to understanding new observations in near-Earth, interplanetary, interstellar, and intergalactic space; in stars, galaxies, and clusters of galaxies, and throughout the observable universe. Physics of the Plasma Universe, 2nd Edition is an update of observations made across the entire cosmic electromagnetic spectrum over the two decades since the publication of the first edition. It addresses paradigm changing discoveries made by telescopes, planetary probes, satellites, and radio and space telescopes. The contents are the result of the author’s 37 years research at Livermore and Los Alamos National Laboratories, and the U.S. Department of Energy.

This book covers topics such as the large-scale structure and the filamentary universe; the formation of magnetic fields and galaxies, active galactic nuclei and quasars, the origin and abundance of light elements, star formation and the evolution of solar systems, and cosmic rays. Chapters 8 and 9 are based on the research of Professor Gerrit Verschuur, and reinvestigation of the manifestation of interstellar neutral hydrogen filaments from radio astronomical observations are given. Using data from the Green Bank 100-m telescope (GBT) of the National Radio Astronomy Observatory (NRAO), detailed information is presented for a non-cosmological origin for the cosmic microwave background quadruple moment.

This volume is aimed at graduate students and researchers active in the areas of cosmic plasmas and space science.

The supercomputer and experimental work was carried out within university, National laboratory, Department of Energy, and supporting NASA facilities.


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Learning Opencv

Learning OpenCV 3
by Adrian Kaehler, Gary Bradski

Get started in the rapidly expanding field of computer vision with this practical guide. Written by Adrian Kaehler and Gary Bradski, creator of the open source OpenCV library, this book provides a thorough introduction for developers, academics, roboticists, and hobbyists. You’ll learn what it takes to build applications that enable computers to “see” and make decisions based on that data.

With over 500 functions that span many areas in vision, OpenCV is used for commercial applications such as security, medical imaging, pattern and face recognition, robotics, and factory product inspection. This book gives you a firm grounding in computer vision and OpenCV for building simple or sophisticated vision applications. Hands-on exercises in each chapter help you apply what you’ve learned.

This volume covers the entire library, in its modern C++ implementation, including machine learning tools for computer vision.

  • Learn OpenCV data types, array types, and array operations
  • Capture and store still and video images with HighGUI
  • Transform images to stretch, shrink, warp, remap, and repair
  • Explore pattern recognition, including face detection
  • Track objects and motion through the visual field
  • Reconstruct 3D images from stereo vision
  • Discover basic and advanced machine learning techniques in OpenCV

Learning OpenCV 3
by Adrian Kaehler, Gary Bradski

Get started in the rapidly expanding field of computer vision with this practical guide. Written by Adrian Kaehler and Gary Bradski, creator of the open source OpenCV library, this book provides a thorough introduction for developers, academics, roboticists, and hobbyists. You’ll learn what it takes to build applications that enable computers to “see” and make decisions based on that data.

With over 500 functions that span many areas in vision, OpenCV is used for commercial applications such as security, medical imaging, pattern and face recognition, robotics, and factory product inspection. This book gives you a firm grounding in computer vision and OpenCV for building simple or sophisticated vision applications. Hands-on exercises in each chapter help you apply what you’ve learned.

This volume covers the entire library, in its modern C++ implementation, including machine learning tools for computer vision.

  • Learn OpenCV data types, array types, and array operations
  • Capture and store still and video images with HighGUI
  • Transform images to stretch, shrink, warp, remap, and repair
  • Explore pattern recognition, including face detection
  • Track objects and motion through the visual field
  • Reconstruct 3D images from stereo vision
  • Discover basic and advanced machine learning techniques in OpenCV

Learning OpenCV
by Gary Bradski, Adrian Kaehler

“This library is useful for practitioners, and is an excellent tool for those entering the field: it is a set of computer vision algorithms that work as advertised.”-William T. Freeman, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology

Learning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators of the free open source OpenCV library, this book introduces you to computer vision and demonstrates how you can quickly build applications that enable computers to “see” and make decisions based on that data.

Computer vision is everywhere-in security systems, manufacturing inspection systems, medical image analysis, Unmanned Aerial Vehicles, and more. It stitches Google maps and Google Earth together, checks the pixels on LCD screens, and makes sure the stitches in your shirt are sewn properly. OpenCV provides an easy-to-use computer vision framework and a comprehensive library with more than 500 functions that can run vision code in real time.

Learning OpenCV will teach any developer or hobbyist to use the framework quickly with the help of hands-on exercises in each chapter. This book includes:

  • A thorough introduction to OpenCV
  • Getting input from cameras
  • Transforming images
  • Segmenting images and shape matching
  • Pattern recognition, including face detection
  • Tracking and motion in 2 and 3 dimensions
  • 3D reconstruction from stereo vision
  • Machine learning algorithms

Getting machines to see is a challenging but entertaining goal. Whether you want to build simple or sophisticated vision applications, Learning OpenCV is the book you need to get started.


Machine Learning for OpenCV
by Michael Beyeler

Expand your OpenCV knowledge and master key concepts of machine learning using this practical, hands-on guide.

About This Book

  • Load, store, edit, and visualize data using OpenCV and Python
  • Grasp the fundamental concepts of classification, regression, and clustering
  • Understand, perform, and experiment with machine learning techniques using this easy-to-follow guide
  • Evaluate, compare, and choose the right algorithm for any task

Who This Book Is For

This book targets Python programmers who are already familiar with OpenCV; this book will give you the tools and understanding required to build your own machine learning systems, tailored to practical real-world tasks.

What You Will Learn

  • Explore and make effective use of OpenCV’s machine learning module
  • Learn deep learning for computer vision with Python
  • Master linear regression and regularization techniques
  • Classify objects such as flower species, handwritten digits, and pedestrians
  • Explore the effective use of support vector machines, boosted decision trees, and random forests
  • Get acquainted with neural networks and Deep Learning to address real-world problems
  • Discover hidden structures in your data using k-means clustering
  • Get to grips with data pre-processing and feature engineering

In Detail

Machine learning is no longer just a buzzword, it is all around us: from protecting your email, to automatically tagging friends in pictures, to predicting what movies you like. Computer vision is one of today’s most exciting application fields of machine learning, with Deep Learning driving innovative systems such as self-driving cars and Google’s DeepMind.

OpenCV lies at the intersection of these topics, providing a comprehensive open-source library for classic as well as state-of-the-art computer vision and machine learning algorithms. In combination with Python Anaconda, you will have access to all the open-source computing libraries you could possibly ask for.

Machine learning for OpenCV begins by introducing you to the essential concepts of statistical learning, such as classification and regression. Once all the basics are covered, you will start exploring various algorithms such as decision trees, support vector machines, and Bayesian networks, and learn how to combine them with other OpenCV functionality. As the book progresses, so will your machine learning skills, until you are ready to take on today’s hottest topic in the field: Deep Learning.

By the end of this book, you will be ready to take on your own machine learning problems, either by building on the existing source code or developing your own algorithm from scratch!

Style and approach

OpenCV machine learning connects the fundamental theoretical principles behind machine learning to their practical applications in a way that focuses on asking and answering the right questions. This book walks you through the key elements of OpenCV and its powerful machine learning classes, while demonstrating how to get to grips with a range of models.


Learning OpenCV 3 Application Development
by Samyak Datta

Build, create, and deploy your own computer vision applications with the power of OpenCV

About This Book

  • This book provides hands-on examples that cover the major features that are part of any important Computer Vision application
  • It explores important algorithms that allow you to recognize faces, identify objects, extract features from images, help your system make meaningful predictions from visual data, and much more
  • All the code examples in the book are based on OpenCV 3.1 – the latest version

Who This Book Is For

This is the perfect book for anyone who wants to dive into the exciting world of image processing and computer vision. This book is aimed at programmers with a working knowledge of C++. Prior knowledge of OpenCV or Computer Vision/Machine Learning is not required.

What You Will Learn

  • Explore the steps involved in building a typical computer vision/machine learning application
  • Understand the relevance of OpenCV at every stage of building an application
  • Harness the vast amount of information that lies hidden in images into the apps you build
  • Incorporate visual information in your apps to create more appealing software
  • Get acquainted with how large-scale and popular image editing apps such as Instagram work behind the scenes by getting a glimpse of how the image filters in apps can be recreated using simple operations in OpenCV
  • Appreciate how difficult it is for a computer program to perform tasks that are trivial for human beings
  • Get to know how to develop applications that perform face detection, gender detection from facial images, and handwritten character (digit) recognition

In Detail

Computer vision and machine learning concepts are frequently used in practical computer vision based projects. If you’re a novice, this book provides the steps to build and deploy an end-to-end application in the domain of computer vision using OpenCV/C++.

At the outset, we explain how to install OpenCV and demonstrate how to run some simple programs. You will start with images (the building blocks of image processing applications), and see how they are stored and processed by OpenCV. You’ll get comfortable with OpenCV-specific jargon (Mat Point, Scalar, and more), and get to know how to traverse images and perform basic pixel-wise operations.

Building upon this, we introduce slightly more advanced image processing concepts such as filtering, thresholding, and edge detection. In the latter parts, the book touches upon more complex and ubiquitous concepts such as face detection (using Haar cascade classifiers), interest point detection algorithms, and feature descriptors. You will now begin to appreciate the true power of the library in how it reduces mathematically non-trivial algorithms to a single line of code!

The concluding sections touch upon OpenCV’s Machine Learning module. You will witness not only how OpenCV helps you pre-process and extract features from images that are relevant to the problems you are trying to solve, but also how to use Machine Learning algorithms that work on these features to make intelligent predictions from visual data!

Style and approach

This book takes a very hands-on approach to developing an end-to-end application with OpenCV. To avoid being too theoretical, the description of concepts are accompanied simultaneously by the development of applications. Throughout the course of the book, the projects and practical, real-life examples are explained and developed step by step in sync with the theory.


Learning OpenCV 3 Computer Vision with Python
by Joe Minichino, Joseph Howse

Unleash the power of computer vision with Python using OpenCV

About This Book

  • Create impressive applications with OpenCV and Python
  • Familiarize yourself with advanced machine learning concepts
  • Harness the power of computer vision with this easy-to-follow guide

Who This Book Is For

Intended for novices to the world of OpenCV and computer vision, as well as OpenCV veterans that want to learn about what’s new in OpenCV 3, this book is useful as a reference for experts and a training manual for beginners, or for anybody who wants to familiarize themselves with the concepts of object classification and detection in simple and understandable terms. Basic knowledge about Python and programming concepts is required, although the book has an easy learning curve both from a theoretical and coding point of view.

What You Will Learn

  • Install and familiarize yourself with OpenCV 3’s Python API
  • Grasp the basics of image processing and video analysis
  • Identify and recognize objects in images and videos
  • Detect and recognize faces using OpenCV
  • Train and use your own object classifiers
  • Learn about machine learning concepts in a computer vision context
  • Work with artificial neural networks using OpenCV
  • Develop your own computer vision real-life application

In Detail

OpenCV 3 is a state-of-the-art computer vision library that allows a great variety of image and video processing operations. Some of the more spectacular and futuristic features such as face recognition or object tracking are easily achievable with OpenCV 3. Learning the basic concepts behind computer vision algorithms, models, and OpenCV’s API will enable the development of all sorts of real-world applications, including security and surveillance.

Starting with basic image processing operations, the book will take you through to advanced computer vision concepts. Computer vision is a rapidly evolving science whose applications in the real world are exploding, so this book will appeal to computer vision novices as well as experts of the subject wanting to learn the brand new OpenCV 3.0.0. You will build a theoretical foundation of image processing and video analysis, and progress to the concepts of classification through machine learning, acquiring the technical know-how that will allow you to create and use object detectors and classifiers, and even track objects in movies or video camera feeds. Finally, the journey will end in the world of artificial neural networks, along with the development of a hand-written digits recognition application.

Style and approach

This book is a comprehensive guide to the brand new OpenCV 3 with Python to develop real-life computer vision applications.


Learning Image Processing with OpenCV
by Gloria Bueno García, Oscar Deniz Suarez, José Luis Espinosa Aranda, Jesus Salido Tercero, Ismael Serrano Gracia, Noelia Vállez Enano

If you are a competent C++ programmer and want to learn the tricks of image processing with OpenCV, then this book is for you. A basic understanding of image processing is required.

Learning OpenCV
by Gary Bradski, Adrian Kaehler

Learning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators of the free open source OpenCV library, this book introduces you to computer vision and demonstrates how you can quickly build applications that enable computers to “see” and make decisions based on that data.

The second edition is updated to cover new features and changes in OpenCV 2.0, especially the C++ interface.

Computer vision is everywhere—in security systems, manufacturing inspection systems, medical image analysis, Unmanned Aerial Vehicles, and more. OpenCV provides an easy-to-use computer vision framework and a comprehensive library with more than 500 functions that can run vision code in real time. Whether you want to build simple or sophisticated vision applications, Learning OpenCV is the book any developer or hobbyist needs to get started, with the help of hands-on exercises in each chapter.

This book includes:

  • A thorough introduction to OpenCV
  • Getting input from cameras
  • Transforming images
  • Segmenting images and shape matching
  • Pattern recognition, including face detection
  • Tracking and motion in 2 and 3 dimensions
  • 3D reconstruction from stereo vision
  • Machine learning algorithms

Learn Computer Vision Using OpenCV
by Sunila Gollapudi

Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples.
The author starts with an introduction to computer vision followed by setting up OpenCV from scratch using Python. The next section discusses specialized image processing and segmentation and how images are stored and processed by a computer. This involves pattern recognition and image tagging using the OpenCV library. Next, you’ll work with object detection, video storage and interpretation, and human detection using OpenCV. Tracking and motion is also discussed in detail. The book also discusses creating complex deep learning models with CNN and RNN. The author finally concludes with recent applications and trends in computer vision.
After reading this book, you will be able to understand and implement computer vision and its applications with OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning architectures work.
What You Will Learn

  • Understand what computer vision is, and its overall application in intelligent automation systems
  • Discover the deep learning techniques required to build computer vision applications
  • Build complex computer vision applications using the latest techniques in OpenCV, Python, and NumPy
  • Create practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysis


Who This Book Is ForThose who have a basic understanding of machine learning and Python and are looking to learn computer vision and its applications.


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Soft Computing & Intelligent Systems

Analysis and Design of Intelligent Systems Using Soft Computing Techniques
by Patricia Melin, Oscar Castillo, Eduardo G. Ramírez, Witold Pedrycz

This book comprises a selection of papers from IFSA 2007 on new methods for ana- sis and design of hybrid intelligent systems using soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including fuzzy logic, n- ral networks, and genetic algorithms, which can be used to produce powerful hybrid intelligent systems for solving problems in pattern recognition, time series prediction, intelligent control, robotics and automation. Hybrid intelligent systems that combine several SC techniques are needed due to the complexity and high dimensionality of real-world problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of these systems, for this reason it is very important to optimize architecture design. The architectures can combine, in different ways, neural networks, fuzzy logic and genetic algorithms, to achieve the ultimate goal of pattern recognition, time series prediction, intelligent control, or other application areas. This book is intended to be a major reference for scientists and engineers interested in applying new computational and mathematical tools to design hybrid intelligent systems. This book can also be used as a reference for graduate courses like the f- lowing: soft computing, intelligent pattern recognition, computer vision, applied ar- ficial intelligence, and similar ones. The book is divided in to twelve main parts. Each part contains a set of papers on a common subject, so that the reader can find similar papers grouped together.

Soft Computing and Intelligent Systems Design
by Fakhreddine Karray, Fakhreddine O. Karray, Clarence W. De Silva

Traditional artificial intelligence (AI) techniques are based around mathematical techniques of symbolic logic, with programming in languages such as Prolog and LISP invented in the 1960s. These are referred to as “crisp” techniques by the soft computing community. The new wave of AI methods seeks inspiration from the world of biology, and is being used to create numerous real-world intelligent systems with the aid of soft computing tools. These new methods are being increasingly taught at the upper end of the curriculum, sometimes as an adjunct to traditional AI courses, and sometimes as a replacement for them. Where a more radical approach is taken and the course is being taught at an introductory level, we have recently published Negnevitsky’s book. Karray and Silva will be suitable for the majority of courses which will be found at an advanced level. Karray and de Silva cover the problem of control and intelligent systems design using soft-computing techniques in an integrated manner. They present both theory and applications, including industrial applications, and the book contains numerous worked examples, problems and case studies. Covering the state-of-the-art in soft-computing techniques, the book gives the reader sufficient knowledge to tackle a wide range of complex systems for which traditional techniques are inadequate.


Intelligent Systems and Soft Computing
by Behnam Azvine, Nader Azarmi, Detlef D. Nauck

Artificial intelligence has, traditionally focused on solving human-centered problems like natural language processing or common-sense reasoning. On the other hand, for a while now soft computing has been applied successfully in areas like pattern recognition, clustering, or automatic control. The papers in this book explore the possibility of bringing these two areas together.
This book is unique in the way it concentrates on building intelligent software systems by combining methods from diverse disciplines, such as fuzzy set theory, neuroscience, agent technology, knowledge discovery, and symbolic artificial intelligence. The first part of the book focuses on foundational aspects and future directions; the second part provides the reader with an overview of recently developed software tools for building flexible intelligent systems; the final section studies developed applications in various fields.

Soft Computing and Intelligent Systems
by Madan M. Gupta

The field of soft computing is emerging from the cutting edge research over the last ten years devoted to fuzzy engineering and genetic algorithms. The subject is being called soft computing and computational intelligence. With acceptance of the research fundamentals in these important areas, the field is expanding into direct applications through engineering and systems science.

This book cover the fundamentals of this emerging filed, as well as direct applications and case studies. There is a need for practicing engineers, computer scientists, and system scientists to directly apply “fuzzy” engineering into a wide array of devices and systems.


Soft Computing and Intelligent Systems
by Madan M. Gupta

Outline of a computational theory of perceptions based on computing with words / L.A. Zadeh — Introduction to soft computing and intelligent control systems / N.K. Sinha and M.M. Gupta — Computational issues in intelligent control / X.D. Koutsoukos and P.J. Antsaklis — Neural networks — a guided tour / S. Haykin — On generating variable structure organization using a genetic algorithm / A.K. Zaidi and A.H. Levis — Evolutionary algorithms and neural networks / R.G.S. Asthana — Neural networks and fuzzy systems / P. Musilek and M.M. Gupta — Fuzzy neural networks / P. Musilek and M.M. Gupta — A cursory look at parallel and distributed architectures and biologically inspired computing / S.K. Basu — Developments in learning control systems / J.X. Xu … [et al.] — Techniques for genetic adaptive control / W.K. Lennon and K.M. Passino — Cooperative behavior of intelligent agents : theory and practice / L. Vlacic, A. Engwirda, and M. Kajitani — Expert systems in process diagnosis …

Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing
by Patricia Melin, Oscar Castillo

This monograph describes new methods for intelligent pattern recognition using soft computing techniques including neural networks, fuzzy logic, and genetic algorithms. Hybrid intelligent systems that combine several soft computing techniques are needed due to the complexity of pattern recognition problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of pattern recognition systems, to achieve the ultimate goal of pattern recognition. This book also shows results of the application of hybrid intelligent systems to real-world problems of face, fingerprint, and voice recognition. This monograph is intended to be a major reference for scientists and engineers applying new computational and mathematical tools to intelligent pattern recognition and can be also used as a textbook for graduate courses in soft computing, intelligent pattern recognition, computer vision, or applied artificial intelligence.


Handbook of Research on Novel Soft Computing Intelligent Algorithms
by Pandian Vasant

As technologies grow more complex, modeling and simulation of new intelligent systems becomes increasingly challenging and nuanced; specifically in diverse fields such as medicine, engineering, and computer science. Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications explores emerging technologies and best practices to effectively address concerns inherent in properly optimizing advanced systems. With applications in areas such as bio-engineering, space exploration, industrial informatics, information security, and nuclear and renewable energies, this exceptional reference will serve as an important tool for decision makers, managers, researchers, economists, and industrialists across a wide range of scientific fields.

International Proceedings on Advances in Soft Computing, Intelligent Systems and Applications
by M. Sreenivasa Reddy, K. Viswanath, Shiva Prasad K.M.

The book focuses on the state-of-the-art technologies pertaining to advances in soft computing, intelligent system and applications. The Proceedings of ASISA 2016 presents novel and original work in soft computing, intelligent system and applications by the experts and budding researchers. These are the cutting edge technologies that have immense application in various fields. The papers discuss many real world complex problems that cannot be easily handled with traditional mathematical methods. The exact solution of the problems at hand can be achieved with soft computing techniques. Soft computing represents a collection of computational techniques inheriting inspiration from evolutionary algorithms, nature inspired algorithms, bio-inspired algorithms, neural networks and fuzzy logic.


Soft Computing Based Modeling in Intelligent Systems
by Valentina Emilia Balas, János Fodor, Annamária R. Várkonyi-Kóczy

The book “Soft Computing Based Modeling in Intelligent Systems”contains the – tended works originally presented at the IEEE International Workshop SOFA 2005 and additional papers. SOFA, an acronym for SOFt computing and Applications, is an international wo- shop intended to advance the theory and applications of intelligent systems and soft computing. Lotfi Zadeh, the inventor of fuzzy logic, has suggested the term “Soft Computing.” He created the Berkeley Initiative of Soft Computing (BISC) to connect researchers working in these new areas of AI. Professor Zadeh participated actively in our wo- shop. Soft Computing techniques are tolerant to imprecision, uncertainty and partial truth. Due to the large variety and complexity of the domain, the constituting methods of Soft Computing are not competing for a comprehensive ultimate solution. Instead they are complementing each other, for dedicated solutions adapted to each specific pr- lem. Hundreds of concrete applications are already available in many domains. Model based approaches offer a very challenging way to integrate a priori knowledge into procedures. Due to their flexibility, robustness, and easy interpretability, the soft c- puting applications will continue to have an exceptional role in our technologies. The applications of Soft Computing techniques in emerging research areas show its mat- ity and usefulness. The IEEE International Workshop SOFA 2005 held Szeged-Hungary and Arad- Romania in 2005 has led to the publication of these two edited volumes. This volume contains Soft Computing methods and applications in modeling, optimisation and prediction.

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Image Processing & Mathematical Morphology

Image Processing and Mathematical Morphology
by Frank Y. Shih

In the development of digital multimedia, the importance and impact of image processing and mathematical morphology are well documented in areas ranging from automated vision detection and inspection to object recognition, image analysis and pattern recognition. Those working in these ever-evolving fields require a solid grasp of basic fundamentals, theory, and related applications—and few books can provide the unique tools for learning contained in this text.

Image Processing and Mathematical Morphology: Fundamentals and Applications is a comprehensive, wide-ranging overview of morphological mechanisms and techniques and their relation to image processing. More than merely a tutorial on vital technical information, the book places this knowledge into a theoretical framework. This helps readers analyze key principles and architectures and then use the author’s novel ideas on implementation of advanced algorithms to formulate a practical and detailed plan to develop and foster their own ideas. The book:

  • Presents the history and state-of-the-art techniques related to image morphological processing, with numerous practical examples
  • Gives readers a clear tutorial on complex technology and other tools that rely on their intuition for a clear understanding of the subject
  • Includes an updated bibliography and useful graphs and illustrations
  • Examines several new algorithms in great detail so that readers can adapt them to derive their own solution approaches

This invaluable reference helps readers assess and simplify problems and their essential requirements and complexities, giving them all the necessary data and methodology to master current theoretical developments and applications, as well as create new ones.


Mathematical Morphology in Image Processing
by Edward Dougherty

Presents the statistical analysis of morphological filters and their automatic optical design, the development of morphological features for image signatures, and the design of efficient morphological algorithms. Extends the morphological paradigm to include other branches of science and mathematics.;This book is designed to be of interest to optical, electrical and electronics, and electro-optic engineers, including image processing, signal processing, machine vision, and computer vision engineers, applied mathematicians, image analysts and scientists and graduate-level students in image processing and mathematical morphology courses.

Mathematical Morphology in Image Processing
by Edward Dougherty

Presents the statistical analysis of morphological filters and their automatic optical design, the development of morphological features for image signatures, and the design of efficient morphological algorithms. Extends the morphological paradigm to include other branches of science and mathematics.;This book is designed to be of interest to optical, electrical and electronics, and electro-optic engineers, including image processing, signal processing, machine vision, and computer vision engineers, applied mathematicians, image analysts and scientists and graduate-level students in image processing and mathematical morphology courses.

Mathematical Morphology and Its Applications to Image Processing
by Jean Serra, Pierre Soille

Mathematical morphology (MM) is a theory for the analysis of spatial structures. It is called morphology since it aims at analysing the shape and form of objects, and it is mathematical in the sense that the analysis is based on set theory, topology, lattice algebra, random functions, etc.
MM is not only a theory, but also a powerful image analysis technique. The purpose of the present book is to provide the image analysis community with a snapshot of current theoretical and applied developments of MM. The book consists of forty-five contributions classified by subject. It demonstrates a wide range of topics suited to the morphological approach.

Hands-on Morphological Image Processing
by Edward R. Dougherty, Roberto A. Lotufo

Morphological image processing, a standard part of the imaging scientist’s toolbox, can be applied to a wide range of industrial applications. Concentrating on applications, this text shows how to analyse the problems and then develop successful algorithms to solve them.

Mathematical Morphology and Its Application to Signal and Image Processing
by Michael H. F. Wilkinson, Jos B.T.M. Roerdink

The 9th ISMM conference covered a very diverse collection of papers, bound together by the central themes of mathematical morphology, namely, the tre- ment of images in terms of set and lattice theory. Notwithstanding this central theme, this ISMM showed increasing interaction with other ?elds of image and signal processing, and several hybrid methods were presented, which combine the strengths of traditional morphological methods with those of, for example, linear ?ltering.This trendis particularlystrong in the emerging?eld of adaptive morphological ?ltering, where the local shape of structuring elements is det- mined by non-morphological techniques. This builds on previous developments of PDE-based methods in morphology and amoebas. In segmentation we see similar advancements, in the development of morphological active contours. Even within morphology itself, diversi?cation is great, and many new areas of research are being opened up. In particular, morphology of graph-based and complex-based image representations are being explored. Likewise, in the we- established area of connected ?ltering we ?nd new theory and new algorithms, but also expansion into the direction of hyperconnected ?lters. New advances in morphological machine learning, multi-valued and fuzzy morphology are also presented. Notwithstanding the often highly theoretical reputation of mathematical morphology, practitioners in this ?eld have always had an eye for the practical.

Mathematical Morphology and Its Applications to Signal and Image Processing
by Jesús Angulo, Santiago Velasco-Forero, Fernand Meyer

This book contains the refereed proceedings of the 13th International Symposium on Mathematical Morphology, ISMM 2017, held in Fontainebleau, France, in May 2017.

The 36 revised full papers presented together with 4 short papers were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections on algebraic theory, max-plus and max-min mathematics; discrete geometry and discrete topology; watershed and graph-based segmentation; trees and hierarchies; topological and graph-based clustering, classification and filtering; connected operators and attribute filters; PDE-based morphology; scale-space representations and nonlinear decompositions; computational morphology; object detection; and biomedical, material science and physical applications.


Mathematical Morphology and Its Applications to Image and Signal Processing
by John Goutsias, Luc Vincent, Dan S. Bloomberg

Mathematical morphology is a powerful methodology for the processing and analysis of geometric structure in signals and images. This book contains the proceedings of the fifth International Symposium on Mathematical Morphology and its Applications to Image and Signal Processing, held June 26-28, 2000, at Xerox PARC, Palo Alto, California. It provides a broad sampling of the most recent theoretical and practical developments of mathematical morphology and its applications to image and signal processing. Areas covered include: decomposition of structuring functions and morphological operators, morphological discretization, filtering, connectivity and connected operators, morphological shape analysis and interpolation, texture analysis, morphological segmentation, morphological multiresolution techniques and scale-spaces, and morphological algorithms and applications.
Audience: The subject matter of this volume will be of interest to electrical engineers, computer scientists, and mathematicians whose research work is focused on the theoretical and practical aspects of nonlinear signal and image processing. It will also be of interest to those working in computer vision, applied mathematics, and computer graphics.

Mathematical Morphology and its Applications to Image and Signal Processing
by Henk J.A.M. Heijmans, Jos Roerdink

This book contains the proceedings of the International Symposium on Mathematical Morphology and its Applications to Image and Signal Processing IV, held June 3-5, 1998, in Amsterdam, The Netherlands. The purpose of the work is to provide the image analysis community with a sampling of recent developments in theoretical and practical aspects of mathematical morphology and its applications to image and signal processing.
Among the areas covered are: digitization and connectivity, skeletonization, multivariate morphology, morphological segmentation, color image processing, filter design, gray-scale morphology, fuzzy morphology, decomposition of morphological operators, random sets and statistical inference, differential morphology and scale-space, morphological algorithms and applications.
Audience: This volume will be of interest to research mathematicians and computer scientists whose work involves mathematical morphology, image and signal processing.

Mathematical Morphology
by Laurent Najman, Hugues Talbot

Mathematical Morphology allows for the analysis and processing of geometrical structures using techniques based on the fields of set theory, lattice theory, topology, and random functions. It is the basis of morphological image processing, and finds applications in fields including digital image processing (DSP), as well as areas for graphs, surface meshes, solids, and other spatial structures. This book presents an up-to-date treatment of mathematical morphology, based on the three pillars that made it an important field of theoretical work and practical application: a solid theoretical foundation, a large body of applications and an efficient implementation.

The book is divided into five parts and includes 20 chapters. The five parts are structured as follows:

  • Part I sets out the fundamental aspects of the discipline, starting with a general introduction, followed by two more theory-focused chapters, one addressing its mathematical structure and including an updated formalism, which is the result of several decades of work.
  • Part II extends this formalism to some non-deterministic aspects of the theory, in particular detailing links with other disciplines such as stereology, geostatistics and fuzzy logic.
  • Part III addresses the theory of morphological filtering and segmentation, featuring modern connected approaches, from both theoretical and practical aspects.
  • Part IV features practical aspects of mathematical morphology, in particular how to deal with color and multivariate data, links to discrete geometry and topology, and some algorithmic aspects; without which applications would be impossible.
  • Part V showcases all the previously noted fields of work through a sample of interesting, representative and varied applications.

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Image Processing & Mathematical Morphology

Image Processing and Mathematical Morphology
by Frank Y. Shih

In the development of digital multimedia, the importance and impact of image processing and mathematical morphology are well documented in areas ranging from automated vision detection and inspection to object recognition, image analysis and pattern recognition. Those working in these ever-evolving fields require a solid grasp of basic fundamentals, theory, and related applications—and few books can provide the unique tools for learning contained in this text.

Image Processing and Mathematical Morphology: Fundamentals and Applications is a comprehensive, wide-ranging overview of morphological mechanisms and techniques and their relation to image processing. More than merely a tutorial on vital technical information, the book places this knowledge into a theoretical framework. This helps readers analyze key principles and architectures and then use the author’s novel ideas on implementation of advanced algorithms to formulate a practical and detailed plan to develop and foster their own ideas. The book:

  • Presents the history and state-of-the-art techniques related to image morphological processing, with numerous practical examples
  • Gives readers a clear tutorial on complex technology and other tools that rely on their intuition for a clear understanding of the subject
  • Includes an updated bibliography and useful graphs and illustrations
  • Examines several new algorithms in great detail so that readers can adapt them to derive their own solution approaches

This invaluable reference helps readers assess and simplify problems and their essential requirements and complexities, giving them all the necessary data and methodology to master current theoretical developments and applications, as well as create new ones.


Mathematical Morphology in Image Processing
by Edward Dougherty

Presents the statistical analysis of morphological filters and their automatic optical design, the development of morphological features for image signatures, and the design of efficient morphological algorithms. Extends the morphological paradigm to include other branches of science and mathematics.;This book is designed to be of interest to optical, electrical and electronics, and electro-optic engineers, including image processing, signal processing, machine vision, and computer vision engineers, applied mathematicians, image analysts and scientists and graduate-level students in image processing and mathematical morphology courses.

Mathematical Morphology in Image Processing
by Edward Dougherty

Presents the statistical analysis of morphological filters and their automatic optical design, the development of morphological features for image signatures, and the design of efficient morphological algorithms. Extends the morphological paradigm to include other branches of science and mathematics.;This book is designed to be of interest to optical, electrical and electronics, and electro-optic engineers, including image processing, signal processing, machine vision, and computer vision engineers, applied mathematicians, image analysts and scientists and graduate-level students in image processing and mathematical morphology courses.

Mathematical Morphology and Its Applications to Image Processing
by Jean Serra, Pierre Soille

Mathematical morphology (MM) is a theory for the analysis of spatial structures. It is called morphology since it aims at analysing the shape and form of objects, and it is mathematical in the sense that the analysis is based on set theory, topology, lattice algebra, random functions, etc.
MM is not only a theory, but also a powerful image analysis technique. The purpose of the present book is to provide the image analysis community with a snapshot of current theoretical and applied developments of MM. The book consists of forty-five contributions classified by subject. It demonstrates a wide range of topics suited to the morphological approach.

Hands-on Morphological Image Processing
by Edward R. Dougherty, Roberto A. Lotufo

Morphological image processing, a standard part of the imaging scientist’s toolbox, can be applied to a wide range of industrial applications. Concentrating on applications, this text shows how to analyse the problems and then develop successful algorithms to solve them.

Mathematical Morphology and Its Application to Signal and Image Processing
by Michael H. F. Wilkinson, Jos B.T.M. Roerdink

The 9th ISMM conference covered a very diverse collection of papers, bound together by the central themes of mathematical morphology, namely, the tre- ment of images in terms of set and lattice theory. Notwithstanding this central theme, this ISMM showed increasing interaction with other ?elds of image and signal processing, and several hybrid methods were presented, which combine the strengths of traditional morphological methods with those of, for example, linear ?ltering.This trendis particularlystrong in the emerging?eld of adaptive morphological ?ltering, where the local shape of structuring elements is det- mined by non-morphological techniques. This builds on previous developments of PDE-based methods in morphology and amoebas. In segmentation we see similar advancements, in the development of morphological active contours. Even within morphology itself, diversi?cation is great, and many new areas of research are being opened up. In particular, morphology of graph-based and complex-based image representations are being explored. Likewise, in the we- established area of connected ?ltering we ?nd new theory and new algorithms, but also expansion into the direction of hyperconnected ?lters. New advances in morphological machine learning, multi-valued and fuzzy morphology are also presented. Notwithstanding the often highly theoretical reputation of mathematical morphology, practitioners in this ?eld have always had an eye for the practical.

Mathematical Morphology and Its Applications to Signal and Image Processing
by Jesús Angulo, Santiago Velasco-Forero, Fernand Meyer

This book contains the refereed proceedings of the 13th International Symposium on Mathematical Morphology, ISMM 2017, held in Fontainebleau, France, in May 2017.

The 36 revised full papers presented together with 4 short papers were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections on algebraic theory, max-plus and max-min mathematics; discrete geometry and discrete topology; watershed and graph-based segmentation; trees and hierarchies; topological and graph-based clustering, classification and filtering; connected operators and attribute filters; PDE-based morphology; scale-space representations and nonlinear decompositions; computational morphology; object detection; and biomedical, material science and physical applications.


Mathematical Morphology and Its Applications to Image and Signal Processing
by John Goutsias, Luc Vincent, Dan S. Bloomberg

Mathematical morphology is a powerful methodology for the processing and analysis of geometric structure in signals and images. This book contains the proceedings of the fifth International Symposium on Mathematical Morphology and its Applications to Image and Signal Processing, held June 26-28, 2000, at Xerox PARC, Palo Alto, California. It provides a broad sampling of the most recent theoretical and practical developments of mathematical morphology and its applications to image and signal processing. Areas covered include: decomposition of structuring functions and morphological operators, morphological discretization, filtering, connectivity and connected operators, morphological shape analysis and interpolation, texture analysis, morphological segmentation, morphological multiresolution techniques and scale-spaces, and morphological algorithms and applications.
Audience: The subject matter of this volume will be of interest to electrical engineers, computer scientists, and mathematicians whose research work is focused on the theoretical and practical aspects of nonlinear signal and image processing. It will also be of interest to those working in computer vision, applied mathematics, and computer graphics.

Mathematical Morphology and its Applications to Image and Signal Processing
by Henk J.A.M. Heijmans, Jos Roerdink

This book contains the proceedings of the International Symposium on Mathematical Morphology and its Applications to Image and Signal Processing IV, held June 3-5, 1998, in Amsterdam, The Netherlands. The purpose of the work is to provide the image analysis community with a sampling of recent developments in theoretical and practical aspects of mathematical morphology and its applications to image and signal processing.
Among the areas covered are: digitization and connectivity, skeletonization, multivariate morphology, morphological segmentation, color image processing, filter design, gray-scale morphology, fuzzy morphology, decomposition of morphological operators, random sets and statistical inference, differential morphology and scale-space, morphological algorithms and applications.
Audience: This volume will be of interest to research mathematicians and computer scientists whose work involves mathematical morphology, image and signal processing.

Mathematical Morphology
by Laurent Najman, Hugues Talbot

Mathematical Morphology allows for the analysis and processing of geometrical structures using techniques based on the fields of set theory, lattice theory, topology, and random functions. It is the basis of morphological image processing, and finds applications in fields including digital image processing (DSP), as well as areas for graphs, surface meshes, solids, and other spatial structures. This book presents an up-to-date treatment of mathematical morphology, based on the three pillars that made it an important field of theoretical work and practical application: a solid theoretical foundation, a large body of applications and an efficient implementation.

The book is divided into five parts and includes 20 chapters. The five parts are structured as follows:

  • Part I sets out the fundamental aspects of the discipline, starting with a general introduction, followed by two more theory-focused chapters, one addressing its mathematical structure and including an updated formalism, which is the result of several decades of work.
  • Part II extends this formalism to some non-deterministic aspects of the theory, in particular detailing links with other disciplines such as stereology, geostatistics and fuzzy logic.
  • Part III addresses the theory of morphological filtering and segmentation, featuring modern connected approaches, from both theoretical and practical aspects.
  • Part IV features practical aspects of mathematical morphology, in particular how to deal with color and multivariate data, links to discrete geometry and topology, and some algorithmic aspects; without which applications would be impossible.
  • Part V showcases all the previously noted fields of work through a sample of interesting, representative and varied applications.

Posted on

Fundamentals Of Wavelets

Fundamentals of Wavelets
by Jaideva C. Goswami, Andrew K. Chan

Most existing books on wavelets are either too mathematical or they focus on too narrow a specialty. This book provides a thorough treatment of the subject from an engineering point of view. It is a one-stop source of theory, algorithms, applications, and computer codes related to wavelets. This second edition has been updated by the addition of:

  • a section on “Other Wavelets” that describes curvelets, ridgelets, lifting wavelets, etc
  • a section on lifting algorithms
  • Sections on Edge Detection and Geophysical Applications
  • Section on Multiresolution Time Domain Method (MRTD) and on Inverse problems

Fundamentals of Wavelets
by Jaideva C. Goswami, Andrew K. Chan

Wavelet theory originated from research activities in many areas of science and engineering. As a result, it finds applications in a wide range of practical problems. Wavelet techniques are specifically suited for nonstationary signals for which classic Fourier methods are ineffective.

Based on courses taught by the authors at Texas A&M University as well as related conferences, Fundamentals of Wavelets is a textbook offering an up-to-date engineering approach to wavelet theory. It balances a discussion of wavelet theory and algorithms with its far-ranging practical applications in signal processing, image processing, electromagnetic wave scattering, and boundary value problems.

In a clear, progressive format, the book describes:
* Basic concepts of linear algebra, Fourier analysis, and discrete signal analysis
* Theoretical aspects of time-frequency analysis and multiresolution analysis
* Construction of various wavelets
* Algorithms for computing wavelet transformations.

Concluding chapters present interesting applications of wavelets to signal processing and boundary value problems. Fundamentals of Wavelets is an essential introduction to wavelet theory for students and professionals alike in a practical, real-world engineering context.


Fundamentals of Wavelets
by Jizheng Di

Many researchers from various scientific disciplines use wavelets, but as often as not they fail to understand the fundamental concepts of wavelet analysis and why wavelets can be used both to solve and to treat problems. Fundamentals of Wavelets is designed to meet the needs of the above-mentioned researchers and to demonstrate that wavelets are not only the microscopes and telescopes in mathematics but that it is also not necessary to have a detailed theoretical knowledge to use them to solve problems.

Wavelets
by John J. Benedetto

Wavelets is a carefully organized and edited collection of extended survey papers addressing key topics in the mathematical foundations and applications of wavelet theory. The first part of the book is devoted to the fundamentals of wavelet analysis. The construction of wavelet bases and the fast computation of the wavelet transform in both continuous and discrete settings is covered. The theory of frames, dilation equations, and local Fourier bases are also presented.

The second part of the book discusses applications in signal analysis, while the third part covers operator analysis and partial differential equations. Each chapter in these sections provides an up-to-date introduction to such topics as sampling theory, probability and statistics, compression, numerical analysis, turbulence, operator theory, and harmonic analysis.
The book is ideal for a general scientific and engineering audience, yet it is mathematically precise. It will be an especially useful reference for harmonic analysts, partial differential equation researchers, signal processing engineers, numerical analysts, fluids researchers, and applied mathematicians.


Wavelets and Subbands
by Agostino Abbate, Casimer DeCusatis, Pankaj K. Das

Recently there has been intense research activity on the subject of wavelet/subband theory and application. Experts in such diverse fields as mathematics, physics, electrical engineering and image processing have provided original and pioneering works and results. But this diversity, while rich and productive, has lead to a sense of fragmentation, especially to those new to the field, and nonspecialists, trying to understand the connections between the different aspects of wavelet and subband theory.

The book is designed to present an understanding of wavelets and their development from a continuous-domain transformation to a frame representation and finally to multiresolution analysis tools such as subband decomposition. The book presents a theoretical understanding of the subject that is intertwined with practical examples and practical applications of wavelets in ultrasonic and biomedical applications. There is special emphasis on applications in communications and compression as well as image processing.

Topics and Features:

* Provides an understanding of the link between continuous wavelet transform, the fast wavelet transform and subband decomposition.

* Algorithms and numerical examples are implemented in Matlab.

* The design of wavelet bases, and how to implement the transform both in hardware and software is discussed in detail.

* Covers the fundamentals and the developments of the links between areas such as time-frequency analysis, digital signal processing, image processing and Fourier and wavelet transform, both continuous and discrete.

Extended mathematical treatment and numerous examples, with particular emphasis to the transition from the continuous domain to multiresolution and subband. The book is an essential text/reference for graduates, researchers, and professionals in electrical engineering, communications engineering and computer engineering. Practitioners and professionals engaged in signal processing, wavelets and Fourier analysis will find the book a useful resource and comprehensive guide.


Wavelets
by Robert X Gao, Ruqiang Yan

Wavelets: Theory and Applications for Manufacturing presents a systematic description of the fundamentals of wavelet transform and its applications. Given the widespread utilization of rotating machines in modern manufacturing and the increasing need for condition-based, as opposed to fix-interval, intelligent maintenance to minimize machine down time and ensure reliable production, it is of critical importance to advance the science base of signal processing in manufacturing. This volume also deals with condition monitoring and health diagnosis of rotating machine components and systems, such as bearings, spindles, and gearboxes, while also: -Providing a comprehensive survey on wavelets specifically related to problems encountered in manufacturing -Discussing the integration of wavelet transforms with other soft computing techniques such as fuzzy logic, for machine defect and severity classification -Showing how to custom design wavelets for improved performance in signal analysis Focusing on wavelet transform as a tool specifically applied and designed for applications in manufacturing, Wavelets: Theory and Applications for Manufacturing presents material appropriate for both academic researchers and practicing engineers working in the field of manufacturing.

Chemometrics
by Foo-Tim Chau, Yi-Zeng Liang, Junbin Gao, Xue-Guang Shao

Wavelet Transformations and Their Applications in Chemistry pioneers a new approach to classifying existing chemometric techniques for data analysis in one and two dimensions, using a practical applications approach to illustrating chemical examples and problems. Written in a simple, balanced, applications-based style, the book is geared to both theorists and non-mathematicians.
This text emphasizes practical applications in chemistry. It employs straightforward language and examples to show the power of wavelet transforms without overwhelming mathematics, reviews other methods, and compares wavelets with other techniques that provide similar capabilities. It uses examples illustrated in MATLAB codes to assist chemists in developing applications, and includes access to a supplementary Web site providing code and data sets for work examples. Wavelet Transformations and Their Applications in Chemistry will prove essential to professionals and students working in analytical chemistry and process chemistry, as well as physical chemistry, spectroscopy, and statistics.

Wavelets in Chemistry
by Beata Walczak

Wavelets seem to be the most efficient tool in signal denoising and compression. They can be used in an unlimited number of applications in all fields of chemistry where the instrumental signals are the source of information about the studied chemical systems or phenomena, and in all cases where these signals have to be archived. The quality of the instrumental signals determines the quality of answer to the basic analytical questions: how many components are in the studied systems, what are these components like and what are their concentrations? Efficient compression of the signal sets can drastically speed up further processing such as data visualization, modelling (calibration and pattern recognition) and library search. Exploration of the possible applications of wavelets in analytical chemistry has just started and this book will significantly speed up the process.
The first part, concentrating on theoretical aspects, is written in a tutorial-like manner, with simple numerical examples. For the reader’s convenience, all basic terms are explained in detail and all unique properties of wavelets are pinpointed and compared with the other types of basis function. The second part presents applications of wavelets from many branches of chemistry which will stimulate chemists to further exploration of this exciting subject.

Foundations of Signal Processing
by Martin Vetterli, Jelena Kovačević, Vivek K Goyal

This comprehensive and engaging textbook introduces the basic principles and techniques of signal processing, from the fundamental ideas of signals and systems theory to real-world applications. Students are introduced to the powerful foundations of modern signal processing, including the basic geometry of Hilbert space, the mathematics of Fourier transforms, and essentials of sampling, interpolation, approximation and compression The authors discuss real-world issues and hurdles to using these tools, and ways of adapting them to overcome problems of finiteness and localization, the limitations of uncertainty, and computational costs. It includes over 160 homework problems and over 220 worked examples, specifically designed to test and expand students’ understanding of the fundamentals of signal processing, and is accompanied by extensive online materials designed to aid learning, including Mathematica® resources and interactive demonstrations.

Wavelet Methods in Statistics with R
by Guy Nason

This book contains information on how to tackle many important problems using a multiscale statistical approach. It focuses on how to use multiscale methods and discusses methodological and applied considerations.