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The focus of this book is on providing a thorough treatment of image processing with an emphasis on those aspects most used in computer graphics. Throughout, the authors concentrate on describing and analysing the underlying concepts rather than on presenting algorithms or pseudocode. As befits a modern introduction to this topic, a healthy balance is struck between discussing the underlying mathematics of the subject and the main topics covered: signal processing, data discretization, the theory of colour and different colour systems, operations in images, dithering and half-toning, warping and morphing, and image processing.
A cookbook of the hottest new algorithms and cutting-edge techniques in image processing and computer vision This amazing book/CD package puts the power of all the hottest new image processing techniques and algorithms in your hands. Based on J. R. Parker's exhaustive survey of Internet newsgroups worldwide, Algorithms for Image Processing and Computer Vision answers the most frequently asked questions with practical solutions. Parker uses dozens of real-life examples taken from fields such as robotics, space exploration, forensic analysis, cartography, and medical diagnostics, to clearly describe the latest techniques for morphing, advanced edge detection, wavelets, texture classification, image restoration, symbol recognition, and genetic algorithms, to name just a few. And, best of all, he implements each method covered in C and provides all the source code on the CD. For the first time, you're rescued from the hours of mind-numbing mathematical calculations it would ordinarily take to program these state-of-the-art image processing capabilities into software. At last, nonmathematicians get all the shortcuts they need for sophisticated image recognition and processing applications. On the CD-ROM you'll find: * Complete code for examples in the book * A gallery of images illustrating the results of advanced techniques * A free GNU compiler that lets you run source code on any platform * A system for restoring damaged or blurred images * A genetic algorithms package
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.
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.
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.
Introduction to Visual Computing: Core Concepts in Computer Vision, Graphics, and Image Processing covers the fundamental concepts of visual computing. Whereas past books have treated these concepts within the context of specific fields such as computer graphics, computer vision or image processing, this book offers a unified view of these core concepts, thereby providing a unified treatment of computational and mathematical methods for creating, capturing, analyzing and manipulating visual data (e.g. 2D images, 3D models). Fundamentals covered in the book include convolution, Fourier transform, filters, geometric transformations, epipolar geometry, 3D reconstruction, color and the image synthesis pipeline. The book is organized in four parts. The first part provides an exposure to different kinds of visual data (e.g. 2D images, videos and 3D geometry) and the core mathematical techniques that are required for their processing (e.g. interpolation and linear regression.) The second part of the book on Image Based Visual Computing deals with several fundamental techniques to process 2D images (e.g. convolution, spectral analysis and feature detection) and corresponds to the low level retinal image processing that happens in the eye in the human visual system pathway. The next part of the book on Geometric Visual Computing deals with the fundamental techniques used to combine the geometric information from multiple eyes creating a 3D interpretation of the object and world around us (e.g. transformations, projective and epipolar geometry, and 3D reconstruction). This corresponds to the higher level processing that happens in the brain combining information from both the eyes thereby helping us to navigate through the 3D world around us. The last two parts of the book cover Radiometric Visual Computing and Visual Content Synthesis. These parts focus on the fundamental techniques for processing information arising from the interaction of light with objects around us, as well as the fundamentals of creating virtual computer generated worlds that mimic all the processing presented in the prior sections. The book is written for a 16 week long semester course and can be used for both undergraduate and graduate teaching, as well as a reference for professionals.
Feature Extraction and Image Processing for Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in Matlab. 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 exemplar code of the algorithms." Fully updated with the latest developments in feature extraction, including expanded tutorials and new techniques, this new edition contains extensive new material on Haar wavelets, Viola-Jones, bilateral filtering, SURF, PCA-SIFT, moving object detection and tracking, development of symmetry operators, LBP texture analysis, Adaboost, and a new appendix on color models. Coverage of distance measures, feature detectors, wavelets, level sets and texture tutorials has been extended. - Named a 2012 Notable Computer Book for Computing Methodologies by Computing Reviews - 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 - The only currently available text to concentrate on feature extraction with working implementation and worked through derivation
This book constitutes the refereed conference proceedings of the ICVGIP 2016 Satellite Workshops, WCVA, DAR, and MedImage, held in Guwahati, India, in December 2016. The papers presented are extended versions of the papers of three of the four workshops: Computer Vision Applications, Document Analysis and Recognition and Medical Image Processing. The Computer Vision Application track received 52 submissions and after a rigorous review process, 18 papers were presented. The focus is mainly on industrial applications of computer vision and related technologies. The Document Analysis and Recognition track received 10 submissions from which 7 papers were selected. The MedImage workshops focuses on problems in medical image computing and received 14 papers from which 9 were accepted for presentation in this book.
"This book brings together various research methodologies and trends in emerging areas of application of computer vision and image processing for those interested in the research developments of this rapidly growing field"--
Tensor signal processing is an emerging field with important applications to computer vision and image processing. This book presents the state of the art in this new branch of signal processing, offering a great deal of research and discussions by leading experts in the area. The wide-ranging volume offers an overview into cutting-edge research into the newest tensor processing techniques and their application to different domains related to computer vision and image processing. This comprehensive text will prove to be an invaluable reference and resource for researchers, practitioners and advanced students working in the area of computer vision and image processing.