Handbook Of Pattern Recognition And Computer Vision 5th Edition
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Handbook of Pattern Recognition and Computer Vision (5th Edition)
The book provides an up-to-date and authoritative treatment of pattern recognition and computer vision, with chapters written by leaders in the field. On the basic methods in pattern recognition and computer vision, topics range from statistical pattern recognition to array grammars to projective geometry to skeletonization, and shape and texture measures. Recognition applications include character recognition and document analysis, detection of digital mammograms, remote sensing image fusion, and analysis of functional magnetic resonance imaging data, etc.
Handbook Of Pattern Recognition And Computer Vision (2nd Edition)
The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.
Hands-On Computer Vision
Author: Marc Pomplun
language: en
Publisher: World Scientific Publishing Company Incorporated
Release Date: 2020-06-15
This book provides its readers the fundamental concepts in computer vision and how to design and implement vision algorithms for given problems. No prior knowledge of computer vision is required, but readers are expected to have experience in computer programming. Commented sample code in the C language and a variety of programming exercises in this book will assist the readers in developing an in-depth understanding of computer vision algorithms and their implementations. All major computer vision topics such as image preprocessing, edge detection, image segmentation, shape representation, texture, object recognition, image understanding, stereo vision, and motion are covered, together with their mathematical foundations and biological counterparts. By additionally providing hands-on experience on building computer vision systems from the ground up, this book will equip the readers with the skills necessary for developing professional vision solutions or conducting computer vision research in graduate schools.