Template Matching Techniques in Computer Vision: Theory and Practice

Front Cover
John Wiley & Sons, Apr 29, 2009 - Science - 348 pages
The detection and recognition of objects in images is a key research topic in the computer vision community. Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling human perception mechanisms, and for the development of practical biometric systems. This book and the accompanying website, focus on template matching, a subset of object recognition techniques of wide applicability, which has proved to be particularly effective for face recognition applications. Using examples from face processing tasks throughout the book to illustrate more general object recognition approaches, Roberto Brunelli:
  • examines the basics of digital image formation, highlighting points critical to the task of template matching;
  • presents basic and advanced template matching techniques, targeting grey-level images, shapes and point sets;
  • discusses recent pattern classification paradigms from a template matching perspective;
  • illustrates the development of a real face recognition system;
  • explores the use of advanced computer graphics techniques in the development of computer vision algorithms.

Template Matching Techniques in Computer Vision is primarily aimed at practitioners working on the development of systems for effective object recognition such as biometrics, robot navigation, multimedia retrieval and landmark detection. It is also of interest to graduate students undertaking studies in these areas.

 

What people are saying - Write a review

User Review - Flag as inappropriate

For feature collection study

Contents

Preface
ix
1 Introduction
1
2 The Imaging Process
9
3 Template Matching as Testing
43
4 Robust Similarity Estimators
73
5 Ordinal Matching Measures
97
6 Matching Variable Patterns
113
7 Matching Linear Structure The Hough Transform
125
9 Deformable Templates
181
10 Computational Aspects of Template Matching
201
11 Matching Point Sets The Hausdorff Distance
221
12 Support Vector Machines and Regularization Networks
237
13 Feature Templates
263
14 Building a Multibiometric System
281
Appendices
293
Index
335

8 Lowdimensionality Representations and Matching
147

Other editions - View all

Common terms and phrases

About the author (2009)

Roberto Brunelli, Senior Researcher, ITC-irst, Italy
Roberto Brunelli is currently working for ITC-irst for the Technologies of Vision Research Line of Interactive Sensory Systems Division. He has held this post since 1987 after gaining his degree in Physics from the University of Trento (Italy). His research activities and interests are in the areas of computer vision tools, analysis of aerial images, the development of algorithms for the compressed description of binary images, optimization, neural networks, face analysis, video analysis and image retrieval. Dr Brunelli's research projects have been implemented in several EU funded projects, and he has also undertaken teaching assignments at the International Doctorate School of the University of Trento. He has written over 30 published journal and conference papers, several of which deal with computational face perception. The paper 'Template Matching: Matched Spatial Filters and Beyond' received a Pattern Recognition Society Award in 1998. He has acted as a referee for some of the major journals on image processing and related techniques, for example Computer Vision and Image Understanding and IEEE Transactions on Image Processing, and has also been on the Technical Committee for several conferences, including Audio- and Video-Based Biometric Person Authentication, IEEE Conference on Computer Vision and Pattern Recognition and European Conference on Computer Vision.

Bibliographic information