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Feature Extraction and Image Processing for Computer Vision

Feature Extraction and Image Processing for Computer Vision
  • Author : Mark Nixon,Alberto Aguado
  • Publisher :Unknown
  • Release Date :2019-11-17
  • Total pages :650
  • ISBN : 9780128149775
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Summary : Feature Extraction for Image Processing and Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the link between theory and exemplar code of the algorithms." Essential background theory is carefully explained. This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation. The only text to concentrate on feature extraction with working implementation and worked through mathematical derivations and algorithmic methods A thorough overview of available feature extraction methods including essential background theory, shape methods, texture and deep learning Up to date coverage of interest point detection, feature extraction and description and image representation (including frequency domain and colour) Good balance between providing a mathematical background and practical implementation Detailed and explanatory of algorithms in MATLAB and Python

Feature Extraction and Image Processing

Feature Extraction and Image Processing
  • Author : Mark Nixon
  • Publisher :Unknown
  • Release Date :2013-10-22
  • Total pages :350
  • ISBN : 9780080506258
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Summary : Focusing on feature extraction while also covering issues and techniques such as image acquisition, sampling theory, point operations and low-level feature extraction, the authors have a clear and coherent approach that will appeal to a wide range of students and professionals. Ideal module text for courses in artificial intelligence, image processing and computer vision Essential reading for engineers and academics working in this cutting-edge field Supported by free software on a companion website

Feature Extraction & Image Processing

Feature Extraction & Image Processing
  • Author : Mark Nixon
  • Publisher :Unknown
  • Release Date :2008-01-08
  • Total pages :424
  • ISBN : 0080556728
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Summary : Whilst other books cover a broad range of topics, Feature Extraction and Image Processing takes one of the prime targets of applied computer vision, feature extraction, and uses it to provide an essential guide to the implementation of image processing and computer vision techniques. Acting as both a source of reference and a student text, the book explains techniques and fundamentals in a clear and concise manner and helps readers to develop working techniques, with usable code provided throughout. The new edition is updated throughout in line with developments in the field, and is revised to focus on mathematical programming in Matlab. Essential reading for engineers and students working in this cutting edge field Ideal module text and background reference for courses in image processing and computer vision

Computer Vision and Image Processing

Computer Vision and Image Processing
  • Author : Manas Kamal Bhuyan
  • Publisher :Unknown
  • Release Date :2019-11-05
  • Total pages :442
  • ISBN : 9781351248389
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Summary : The book familiarizes readers with fundamental concepts and issues related to computer vision and major approaches that address them. The focus of the book is on image acquisition and image formation models, radiometric models of image formation, image formation in the camera, image processing concepts, concept of feature extraction and feature selection for pattern classification/recognition, and advanced concepts like object classification, object tracking, image-based rendering, and image registration. Intended to be a companion to a typical teaching course on computer vision, the book takes a problem-solving approach.

Algorithms for Image Processing and Computer Vision

Algorithms for Image Processing and Computer Vision
  • Author : J. R. Parker
  • Publisher :Unknown
  • Release Date :2010-11-29
  • Total pages :504
  • ISBN : 1118021886
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Summary : A cookbook of algorithms for common image processing applications Thanks to advances in computer hardware and software, algorithms have been developed that support sophisticated image processing without requiring an extensive background in mathematics. This bestselling book has been fully updated with the newest of these, including 2D vision methods in content-based searches and the use of graphics cards as image processing computational aids. It’s an ideal reference for software engineers and developers, advanced programmers, graphics programmers, scientists, and other specialists who require highly specialized image processing. Algorithms now exist for a wide variety of sophisticated image processing applications required by software engineers and developers, advanced programmers, graphics programmers, scientists, and related specialists This bestselling book has been completely updated to include the latest algorithms, including 2D vision methods in content-based searches, details on modern classifier methods, and graphics cards used as image processing computational aids Saves hours of mathematical calculating by using distributed processing and GPU programming, and gives non-mathematicians the shortcuts needed to program relatively sophisticated applications. Algorithms for Image Processing and Computer Vision, 2nd Edition provides the tools to speed development of image processing applications.

Handbook of Image Processing and Computer Vision

Handbook of Image Processing and Computer Vision
  • Author : Arcangelo Distante,Cosimo Distante
  • Publisher :Unknown
  • Release Date :2020-05-28
  • Total pages :491
  • ISBN : 9783030381486
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Summary : Across three volumes, the Handbook of Image Processing and Computer Vision presents a comprehensive review of the full range of topics that comprise the field of computer vision, from the acquisition of signals and formation of images, to learning techniques for scene understanding. The authoritative insights presented within cover all aspects of the sensory subsystem required by an intelligent system to perceive the environment and act autonomously. Volume 1 (From Energy to Image) examines the formation, properties, and enhancement of a digital image. Topics and features: • Describes the fundamental processes in the field of artificial vision that enable the formation of digital images from light energy • Covers light propagation, color perception, optical systems, and the analog-to-digital conversion of the signal • Discusses the information recorded in a digital image, and the image processing algorithms that can improve the visual qualities of the image • Reviews boundary extraction algorithms, key linear and geometric transformations, and techniques for image restoration • Presents a selection of different image segmentation algorithms, and of widely-used algorithms for the automatic detection of points of interest • Examines important algorithms for object recognition, texture analysis, 3D reconstruction, motion analysis, and camera calibration • Provides an introduction to four significant types of neural network, namely RBF, SOM, Hopfield, and deep neural networks This all-encompassing survey offers a complete reference for all students, researchers, and practitioners involved in developing intelligent machine vision systems. The work is also an invaluable resource for professionals within the IT/software and electronics industries involved in machine vision, imaging, and artificial intelligence. Dr. Cosimo Distante is a Research Scientist in Computer Vision and Pattern Recognition in the Institute of Applied Sciences and Intelligent Systems (ISAI) at the Italian National Research Council (CNR). Dr. Arcangelo Distante is a researcher and the former Director of the Institute of Intelligent Systems for Automation (ISSIA) at the CNR. His research interests are in the fields of Computer Vision, Pattern Recognition, Machine Learning, and Neural Computation.

Image Processing, Computer Vision, and Pattern Recognition

Image Processing, Computer Vision, and Pattern Recognition
  • Author : Hamid R. Arabnia,Leonidas Deligiannidis,Fernando G. Tinetti
  • Publisher :Unknown
  • Release Date :2020-03-13
  • Total pages :168
  • ISBN : 1601325061
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Summary : Proceedings of the 2019 International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV'19) held July 29th - August 1st, 2019 in Las Vegas, Nevada.

Computer Vision and Image Processing

Computer Vision and Image Processing
  • Author : Linda Shapiro
  • Publisher :Unknown
  • Release Date :1992-04-27
  • Total pages :638
  • ISBN : 9780323141567
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Summary : Computer Vision and Image Processing contains review papers from the Computer Vision, Graphics, and Image Processing volume covering a large variety of vision-related topics. Organized into five parts encompassing 26 chapters, the book covers topics on image-level operations and architectures; image representation and recognition; and three-dimensional imaging. The introductory part of this book is concerned with the end-to-end performance of image gathering and processing for high-resolution edge detection. It proposes methods using mathematical morphology to provide a complete edge detection process that may be used with any slope approximating operator. This part also discusses the automatic control of low-level robot vision, presents an image partitioning method suited for parallel implementation, and describes invariant architectures for low-level vision. The subsequent two sections present significant topics on image representation and recognition. Topics covered include the use of the primitives chain code; the geometric properties of the generalized cone; efficient rendering and structural-statistical character recognition algorithms; multi-level thresholding for image segmentation; knowledge-based object recognition system; and shape decomposition method based on perceptual structure. The fourth part describes a rule-based expert system for recovering three-dimensional shape and orientation. A procedure of intensity-guided range sensing to gain insights on the concept of cooperative-and-iterative strategy is also presented in this part. The concluding part contains supplementary texts on texture segmentation using topographic labels and an improved algorithm for labeling connected components in a binary image. Additional algorithms for three-dimensional motion parameter determination and surface tracking in three-dimensional binary images are also provided.

Deep Learning for Vision Systems

Deep Learning for Vision Systems
  • Author : Mohamed Elgendy
  • Publisher :Unknown
  • Release Date :2020-11-10
  • Total pages :480
  • ISBN : 9781617296192
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Summary : How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. Summary Computer vision is central to many leading-edge innovations, including self-driving cars, drones, augmented reality, facial recognition, and much, much more. Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL). Deep Learning for Vision Systems teaches you the concepts and tools for building intelligent, scalable computer vision systems that can identify and react to objects in images, videos, and real life. With author Mohamed Elgendy's expert instruction and illustration of real-world projects, you’ll finally grok state-of-the-art deep learning techniques, so you can build, contribute to, and lead in the exciting realm of computer vision! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology How much has computer vision advanced? One ride in a Tesla is the only answer you’ll need. Deep learning techniques have led to exciting breakthroughs in facial recognition, interactive simulations, and medical imaging, but nothing beats seeing a car respond to real-world stimuli while speeding down the highway. About the book How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. What's inside Image classification and object detection Advanced deep learning architectures Transfer learning and generative adversarial networks DeepDream and neural style transfer Visual embeddings and image search About the reader For intermediate Python programmers. About the author Mohamed Elgendy is the VP of Engineering at Rakuten. A seasoned AI expert, he has previously built and managed AI products at Amazon and Twilio. Table of Contents PART 1 - DEEP LEARNING FOUNDATION 1 Welcome to computer vision 2 Deep learning and neural networks 3 Convolutional neural networks 4 Structuring DL projects and hyperparameter tuning PART 2 - IMAGE CLASSIFICATION AND DETECTION 5 Advanced CNN architectures 6 Transfer learning 7 Object detection with R-CNN, SSD, and YOLO PART 3 - GENERATIVE MODELS AND VISUAL EMBEDDINGS 8 Generative adversarial networks (GANs) 9 DeepDream and neural style transfer 10 Visual embeddings

Feature Extraction & Image Processing, 2nd Edition

Feature Extraction & Image Processing, 2nd Edition
  • Author : Mark Nixon,Alberto Aguado
  • Publisher :Unknown
  • Release Date :2008
  • Total pages :424
  • ISBN : OCLC:1192537907
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Summary : * Essential reading for engineers and students working in this cutting edge field * Ideal module text and background reference for courses in image processing and computer vision * Companion website includes worksheets, links to free software, Matlab files and new demonstrations Image processing and computer vision are currently hot topics with undergraduates and professionals alike. Feature Extraction and Image Processing provides an essential guide to the implementation of image processing and computer vision techniques, explaining techniques and fundamentals in a clear and concise manner. Readers can develop working techniques, with usable code provided throughout and working Matlab and Mathcad files on the web. Focusing on feature extraction while also covering issues and techniques such as image acquisition, sampling theory, point operations and low-level feature extraction, the authors have a clear and coherent approach that will appeal to a wide range of students and professionals. The new edition includes: * New coverage of curvature in low-level feature extraction (SIFT and saliency) and features (phase congruency); geometric active contours; morphology; camera models * Updated coverage of image smoothing (anistropic diffusion); skeletonization; edge detection; curvature; shape descriptions (moments) * Essential reading for engineers and students working in this cutting edge field * Ideal module text and background reference for courses in image processing and computer vision * Companion website includes worksheets, links to free software, Matlab files and solutions.

Deep Learning in Computer Vision

Deep Learning in Computer Vision
  • Author : Mahmoud Hassaballah,Ali Ismail Awad
  • Publisher :Unknown
  • Release Date :2020-03-23
  • Total pages :322
  • ISBN : 9781351003810
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Summary : Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such as accelerating the convolutional neural network inference on field-programmable gate arrays, fire detection in surveillance applications, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision, tumor detection, and skin lesion segmentation as well as skin melanoma classification. The content of this book has been organized such that each chapter can be read independently from the others. The book is a valuable companion for researchers, for postgraduate and possibly senior undergraduate students who are taking an advanced course in related topics, and for those who are interested in deep learning with applications in computer vision, image processing, and pattern recognition.

Digital Image Processing and Analysis

Digital Image Processing and Analysis
  • Author : Scott E Umbaugh
  • Publisher :Unknown
  • Release Date :2010-11-19
  • Total pages :977
  • ISBN : 9781439802052
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Summary : Whether for computer evaluation of otherworldly terrain or the latest high definition 3D blockbuster, digital image processing involves the acquisition, analysis, and processing of visual information by computer and requires a unique skill set that has yet to be defined a single text. Until now. Taking an applications-oriented, engineering approach, Digital Image Processing and Analysis provides the tools for developing and advancing computer and human vision applications and brings image processing and analysis together into a unified framework. Providing information and background in a logical, as-needed fashion, the author presents topics as they become necessary for understanding the practical imaging model under study. He offers a conceptual presentation of the material for a solid understanding of complex topics and discusses the theory and foundations of digital image processing and the algorithm development needed to advance the field. With liberal use of color through-out and more materials on the processing of color images than the previous edition, this book provides supplementary exercises, a new chapter on applications, and two major new tools that allow for batch processing, the analysis of imaging algorithms, and the overall research and development of imaging applications. It includes two new software tools, the Computer Vision and Image Processing Algorithm Test and Analysis Tool (CVIP-ATAT) and the CVIP Feature Extraction and Pattern Classification Tool (CVIP-FEPC). Divided into five major sections, this book provides the concepts and models required to analyze digital images and develop computer vision and human consumption applications as well as all the necessary information to use the CVIPtools environment for algorithm development, making it an ideal reference tool for this fast growing field.

Robotics, Vision and Control

Robotics, Vision and Control
  • Author : Peter Corke
  • Publisher :Unknown
  • Release Date :2011-09-05
  • Total pages :570
  • ISBN : 9783642201448
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Summary : The author has maintained two open-source MATLAB Toolboxes for more than 10 years: one for robotics and one for vision. The key strength of the Toolboxes provide a set of tools that allow the user to work with real problems, not trivial examples. For the student the book makes the algorithms accessible, the Toolbox code can be read to gain understanding, and the examples illustrate how it can be used —instant gratification in just a couple of lines of MATLAB code. The code can also be the starting point for new work, for researchers or students, by writing programs based on Toolbox functions, or modifying the Toolbox code itself. The purpose of this book is to expand on the tutorial material provided with the toolboxes, add many more examples, and to weave this into a narrative that covers robotics and computer vision separately and together. The author shows how complex problems can be decomposed and solved using just a few simple lines of code, and hopefully to inspire up and coming researchers. The topics covered are guided by the real problems observed over many years as a practitioner of both robotics and computer vision. It is written in a light but informative style, it is easy to read and absorb, and includes a lot of Matlab examples and figures. The book is a real walk through the fundamentals of robot kinematics, dynamics and joint level control, then camera models, image processing, feature extraction and epipolar geometry, and bring it all together in a visual servo system. Additional material is provided at http://www.petercorke.com/RVC

Image Feature Detectors and Descriptors

Image Feature Detectors and Descriptors
  • Author : Ali Ismail Awad,Mahmoud Hassaballah
  • Publisher :Unknown
  • Release Date :2016-02-22
  • Total pages :438
  • ISBN : 9783319288543
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Summary : This book provides readers with a selection of high-quality chapters that cover both theoretical concepts and practical applications of image feature detectors and descriptors. It serves as reference for researchers and practitioners by featuring survey chapters and research contributions on image feature detectors and descriptors. Additionally, it emphasizes several keywords in both theoretical and practical aspects of image feature extraction. The keywords include acceleration of feature detection and extraction, hardware implantations, image segmentation, evolutionary algorithm, ordinal measures, as well as visual speech recognition.

A Beginner's Guide to Image Shape Feature Extraction Techniques

A Beginner's Guide to Image Shape Feature Extraction Techniques
  • Author : Jyotismita Chaki,Nilanjan Dey
  • Publisher :Unknown
  • Release Date :2019-08-29
  • Total pages :152
  • ISBN : 0367254395
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Summary : This book emphasizes various image shape feature extraction methods which are necessary for image shape recognition and classification. Focussing on a shape feature extraction technique used in content-based image retrieval (CBIR), it explains different applications of image shape features in the field of content-based image retrieval. Showcasing useful applications and illustrating examples in many interdisciplinary fields, the present book is aimed at researchers and graduate students in electrical engineering, data science, computer science, medicine, and machine learning including medical physics and information technology.

Computer Imaging

Computer Imaging
  • Author : Scott E Umbaugh
  • Publisher :Unknown
  • Release Date :2005-01-27
  • Total pages :688
  • ISBN : 0849329191
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Summary : Computer Imaging: Digital Image Analysis and Processing brings together analysis and processing in a unified framework, providing a valuable foundation for understanding both computer vision and image processing applications. Taking an engineering approach, the text integrates theory with a conceptual and application-oriented style, allowing you to immediately understand how each topic fits into the overall structure of practical application development. Divided into five major parts, the book begins by introducing the concepts and definitions necessary to understand computer imaging. The second part describes image analysis and provides the tools, concepts, and models required to analyze digital images and develop computer vision applications. Part III discusses application areas for the processing of images, emphasizing human visual perception. Part IV delivers the information required to apply a CVIPtools environment to algorithm development. The text concludes with appendices that provide supplemental imaging information and assist with the programming exercises found in each chapter. The author presents topics as needed for understanding each practical imaging model being studied. This motivates the reader to master the topics and also makes the book useful as a reference. The CVIPtools software integrated throughout the book, now in a new Windows version, provides practical examples and encourages you to conduct additional exploration via tutorials and programming exercises provided with each chapter.

Computer Vision and Image Processing

Computer Vision and Image Processing
  • Author : Satish Kumar Singh
  • Publisher :Unknown
  • Release Date :2021
  • Total pages :229
  • ISBN : 9789811610929
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Summary :

Information Theory in Computer Vision and Pattern Recognition

Information Theory in Computer Vision and Pattern Recognition
  • Author : Francisco Escolano Ruiz,Pablo Suau Pérez,Boyán Ivanov Bonev
  • Publisher :Unknown
  • Release Date :2009-07-14
  • Total pages :364
  • ISBN : 9781848822979
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Summary : Information theory has proved to be effective for solving many computer vision and pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feature selection, optimal classifier design and many others). Nowadays, researchers are widely bringing information theory elements to the CVPR arena. Among these elements there are measures (entropy, mutual information...), principles (maximum entropy, minimax entropy...) and theories (rate distortion theory, method of types...). This book explores and introduces the latter elements through an incremental complexity approach at the same time where CVPR problems are formulated and the most representative algorithms are presented. Interesting connections between information theory principles when applied to different problems are highlighted, seeking a comprehensive research roadmap. The result is a novel tool both for CVPR and machine learning researchers, and contributes to a cross-fertilization of both areas.

Computer Vision

Computer Vision
  • Author : Richard Szeliski
  • Publisher :Unknown
  • Release Date :2010-09-30
  • Total pages :812
  • ISBN : 1848829353
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Summary : Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques. Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

Applications of Hybrid Metaheuristic Algorithms for Image Processing

Applications of Hybrid Metaheuristic Algorithms for Image Processing
  • Author : Diego Oliva,Salvador Hinojosa
  • Publisher :Unknown
  • Release Date :2020-03-27
  • Total pages :490
  • ISBN : 9783030409777
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Summary : This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects using complex approaches and medical applications. The book also discusses the theory of the methodologies used to provide an overview of the applications of these tools in image processing. The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence. Further, it is a valuable resource for researchers from the evolutionary computation, artificial intelligence and image processing communities.

Arduino Computer Vision Programming

Arduino Computer Vision Programming
  • Author : Özen Özkaya,Giray Yıllıkçı
  • Publisher :Unknown
  • Release Date :2015-08-28
  • Total pages :222
  • ISBN : 9781782174288
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Summary : Design and develop real-world computer vision applications with the powerful combination of OpenCV and Arduino About This Book Load and run the applications in Arduino to develop intelligent systems Design and implement detection, classification, and recognition algorithms for computer vision applications Explore the best practices of computer vision development including state of the art algorithms and hands-on example projects Who This Book Is For If you are a consumer and hobbyist who has familiarity with the basics of Arduino and wish to learn computer vision programming with Arduino to create intelligent systems, then this book is for you. No knowledge of computer vision programming is required. What You Will Learn Understand the design blocks and the generic architecture of computer vision systems by learning an efficient approach to modelling Build up your skill set of computer vision system design using OpenCV by learning fundamentals, camera selection, data acquisition, filtering, processing, feature extraction and recognition for any specific problem Learn the wired and wireless communication capabilities of Arduino and comprehensive best practices to connect it to the OpenCV environment in a platform-independent way Discover how to use Arduino to elegantly interact with real life via physical actions Solidify everything you've learnt by designing and building a computer vision-enabled practical robot from scratch In Detail Most technologies are developed with an inspiration of human capabilities. Most of the time, the hardest to implement capability is vision. Development of highly capable computer vision applications in an easy way requires a generic approach. In this approach, Arduino is a perfect tool for interaction with the real world. Moreover, the combination of OpenCV and Arduino boosts the level and quality of practical computer vision applications. Computer vision is the next level of sensing the environment. The purpose of this book is to teach you how to develop Arduino-supported computer vision systems that can interact with real life by seeing it. This book will combine the powers of Arduino and computer vision in a generalized, well-defined, and applicable way. The practices and approaches in the book can be used for any related problems and on any platforms. At the end of the book, you should be able to solve any types of real life vision problems with all its components by using the presented approach. Each component will extend your vision with the best practices on the topic. In each chapter, you will find interesting real life practical application examples about the topics in the chapter. To make it grounded, we will build a vision-enabled robot step by step towards the end of the book. You will observe that, even though the contexts of the problems are very different, the approaches to solve them are the same and very easy! Style and approach This book is a step-by-step guide that explains each topic sequentially by using best practices and useful tips to build computer-vision applications with OpenCV and Arduino. All the information in the book is combined in a real life all-in-one example application.