Shape Detection In Computer Vision Using The Hough Transform

Shape detection techniques are an important aspect of computer vision and are used to transform raw image data into the symbolic representations needed for object recognition and location. However, the availability and application of research data relating to shape detection has traditionally been limited by a lack of computational and mathematical skill on the part of the intended end-user. As a result progress in areas such as the automation of visual inspection techniques, where shape detection couls play a pivotal role, has been relatively slow. In this volume, Violet Leavers, an established author and researcher in the field, examines the Hough Transform, a technique which is particularly relevant to industrial applications. By making computational recipes and advice available to the non-specialist, the book aims to popularize the technique, and to provide a bridge between low level computer vision tasks and specialist applications. In addition, Shape Detection in Computer Vision Using the Hough Transform assesses practical and theoretical issues which were previously only available in scientific literature in a way which is easily accessible to the non-specialist user. Shape Detection in Computer Vision Using the Hough Transform fills an obvious gap in the existing market. It is an important textbook which will provide postgraduate students with a thorough grounding in the field, and will also be of interest to junior research staff and program designers.

This is an up-to-date volume of selected and expanded papers originating from Vision Interface 88, a conference held in Edmonton, Canada. A broad range of topics are covered-from image processing to hardware design. They include robot vision, biomedical imaging, remote sensing and parallel processing, shape recognition and features, computational methods in vision, and three dimensional vision and application.

This book constitutes the refereed proceedings of the 8th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2006, held in Antwerp, Belgium in September 2006.The 45 revised full papers and 65 revised poster papers presented were carefully reviewed and selected from around 242 submissions. The papers are organized in topical sections on noise reduction and restoration, segmentation, motion estimation and tracking, video processing and coding, camera calibration, image registration and stereo matching, biometrics and security, medical imaging, image retrieval and image understanding, as well as classification and recognition.

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

The book offers a thorough introduction to machine vision. It is organized in two parts. The first part covers the image acquisition, which is the crucial component of most automated visual inspection systems. All important methods are described in great detail and are presented with a reasoned structure. The second part deals with the modeling and processing of image signals and pays particular regard to methods, which are relevant for automated visual inspection.

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

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

Intelligent recognition methods have recently proven to be indispensable in a variety of modern industries, including computer vision, robotics, medical imaging, visualization and the media. Furthermore, they play a critical role in the traditional fields such as character recognition, natural language processing and personal identification. This cutting-edge book draws together the latest findings of industry experts and researchers from around the globe. It is a timely guide for all those require comprehensive, state-of-the-art advice on the present status and future potential of intelligent recognition technology. Computer-Aided Intelligent Recognition Techniques and Applications: Provides the user community with systems and tools for application in a very wide range of areas, including: IT, education, security, banking, police, postal services, manufacturing, mining, medicine, multimedia, entertainment, communications, data visualization, knowledge extraction, pattern classification and virtual reality. Disseminates information in a plethora of disciplines, for example pattern recognition, AI, image processing, computer vision and graphics, neural networks, cryptography, fuzzy logic, databases, evolutionary algorithms, shape and numerical analysis. Illustrates all theory with real-world examples and case studies. This valuable resource is essential reading for computer scientists, engineers, and consultants requiring up-to-date comprehensive guidance on the latest developments in computer-aided intelligent recognition techniques and applications. Its detailed, practical approach will be of interest to senior undergraduate and graduate students as well as researchers and industry experts in the field of intelligent recognition.