Overview

This volume introduces the fundamental concepts and tools involved in the design and implementation of object recognition systems. Divided into three parts, it first introduces the topic and covers the acquisition of images, then details 3-D object reconstruction, modelling and matching, and finally describes typical recognition systems using case studies. Key features include: Extensive literature surveys of state-of-the-art systems An FTP site from which readers can obtain the MATLAB codes used to generate some of the results found in the text: ftp://ftp. springer. de/pub/cs/object_recognition/ Object Recognition will be essential reading for research scientists, advanced undergraduate and postgraduate students in computer vision, image processing and pattern classification. It will also be of interest to practitioners working in the field of computer vision.

Full Product Details

Author:   M. Bennamoun ,  G.J. Mamic
Publisher:   Springer London Ltd
Imprint:   Springer London Ltd
Edition:   2002 ed.
Dimensions:   Width: 15.50cm , Height: 2.00cm , Length: 23.50cm
Weight:   1.530kg
ISBN:  

9781852333980

ISBN 10:   1852333987
Pages:   350
Publication Date:   12 December 2001
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

A — Introduction and Acquisition Systems.- 1. Introduction.- 2. Stereo Matching and Reconstruction of a Depth Map.- A — Summary.- B — Database Creation and Modelling for 3-D Object Recognition.- 3. 3-D Object Creation for Recognition.- 4. Object Representation and Feature Matching.- B — Summary.- C — Vision Systems — Case Studies.- 5. Optical Character Recognition.- 6. Recognition by Parts and Part Segmentation Techniques.- 7. 3-D Object Recognition Systems.- C — Summary.- Appendices.- A. Vector and Matrix Analysis.- A.1 Preliminaries.- A.1.1 Determinant.- A.1.2 Inversion.- A.2 Derivatives and Integrals of Matrices.- A.3 Vectors and Vector Analysis.- A.4 Eigenvalues and Eigenvectors.- A.5 Quadratic Forms.- B. Principal Component Analysis.- C. Optimisation Fundamentals.- C.1 Fundamental Concepts.- C.2 Linear Least Squares.- C.3 Non-linear Optimisation.- C.4 Direct Search Techniques.- C.4.1 Simplex Method.- C.5 Gradient Methods.- C.5.1 Newton-Raphson Technique.- C.5.2 Davidon-Fletcher-Powell.- C.6 Simulated Annealing.- D. Differential Geometry — Basic Principles.- E. Spline Theory.- E.1 Spline Definitions.- F. Detailed Derivation of Registration Equations.- References.

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