Template Matching Techniques in Computer Vision (eBook)

Theory and Practice

Roberto Brunelli (Autor)

eBook Download: PDF

2009 | 1. Auflage
348 Seiten
John Wiley & Sons (Verlag)
978-0-470-74404-8 (ISBN)

Infos

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.

Autor

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.

Inhalt

Preface

1 Introduction

1.1 Template Matching and Computer Vision

1.2 The Book

1.3 Bibliographical Remarks

References

2 The Imaging Process

2.1 Image Creation

2.2 Biological Eyes

2.3 Digital Eyes

2.4 Digital Image Representations

2.5 Bibliographical Remarks

References

3 Template Matching as Testing

3.1 Detection and Estimation

3.2 Hypothesis Testing

3.3 An Important Example

3.4 A Signal Processing Perspective: Matched Filters

3.5 Pattern Variability and the Normalized Correlation Coefficient

3.6 Estimation

3.7 Bibliographical Remarks

References

4 Robust Similarity Estimators

4.1 Robustness Measures

4.2 M-estimators

4.3 L1 Similarity Measures

4.4 Robust Estimation of Covariance Matrices

4.5 Bibliographical Remarks

References

5 Ordinal Matching Measures

5.1 Ordinal Correlation Measures

5.2 Non-parametric Local Transforms

5.3 Bibliographical Remarks

References

6 Matching Variable Patterns

6.1 Multiclass Synthetic Discriminant Functions

6.2 Advanced Synthetic Discriminant Functions

6.3 Non-orthogonal Image Expansion

6.4 Bibliographical Remarks

References

7 Matching Linear Structure: The Hough Transform

7.1 Getting Shapes: Edge Detection

7.2 The Radon Transform

7.3 The Hough Transform: Line and Circle Detection

7.4 The Generalized Hough Transform

7.5 Bibliographical Remarks

References

8 Low-dimensionality Representations and Matching

8.1 Principal Components

8.2 A Nonlinear Approach: Kernel PCA

8.3 Independent Components

8.4 Linear Discriminant Analysis

8.5 A Sample Application: Photographic-quality Facial Composites

8.6 Bibliographical Remarks

References

9 Deformable Templates

9.1 A Dynamic Perspective on the Hough Transform

9.2 Deformable Templates

9.3 Active Shape Models

9.4 Diffeomorphic Matching

9.5 Bibliographical Remarks

References

10 Computational Aspects of Template Matching

10.1 Speed

10.2 Precision

10.3 Bibliographical Remarks

References

11 Matching Point Sets: The Hausdorff Distance

11.1 Metric Pattern Spaces

11.2 Hausdorff Matching

11.3 Efficient Computation of the Hausdorff Distance

11.4 Partial Hausdorff Matching

11.5 Robustness Aspects

11.6 A Probabilistic Perspective

11.7 Invariant Moments

11.8 Bibliographical Remarks

References

12 Support Vector Machines and Regularization Networks

12.1 Learning and Regularization

12.2 RBF Networks

12.3 Support Vector Machines

12.4 Bibliographical Remarks

References

13 Feature Templates

13.1 Detecting Templates by Features

13.2 Parametric Feature Manifolds

13.3 Multiclass Pattern Rejection

13.4 Template Features

13.5 Bibliographical Remarks

References

14 Building a Multibiometric System

14.1 Systems

14.2 The Electronic Librarian

14.3 Score Integration

14.4 Rejection

14.5 Bibliographical Remarks

References

Appendices

A AnImAl: A Software Environment for Fast Prototyping

A.1 AnImAl: An Image Algebra

A.2 Image Representation and Processing Abstractions

A.3 The AnImAl Environment

A.4 Bibliographical Remarks

References

B Synthetic Oracles for Algorithm Development

B.1 Computer Graphics

B.2 Describing Reality: Flexible Rendering Languages

B.3 Bibliographical Remarks

References

C On Evaluation

C.1 A Note on Performance Evaluation

C.2 Training a Classifier

C.3 Analyzing the Performance of a Classifier

C.4 Evaluating a Technology

C.5 Bibliographical Remarks

References

Index

Produkt-Details

• Erscheint lt. Verlag: 29.4.2009
• Sprache: englisch
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Naturwissenschaften ► Physik / Astronomie ► Mechanik
• Themenwelt: Technik ► Elektrotechnik / Energietechnik
• Schlagworte: Bildgebende Systeme u. Verfahren • Electrical & Electronics Engineering • Elektrotechnik u. Elektronik • Imaging Systems & Technology • Signal Processing • Signalverarbeitung
• ISBN-10: 0-470-74404-9 / 0470744049
• ISBN-13: 978-0-470-74404-8 / 9780470744048