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Handbook of Computer Vision Algorithms in Image Algebra
by Gerhard X. Ritter; Joseph N. Wilson
CRC Press, CRC Press LLC
ISBN: 0849326362 Pub Date: 05/01/96
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Table of Contents
Preface
The aim of this book is to acquaint engineers, scientists, and students with the basic concepts of image algebra
and its use in the concise representation of computer vision algorithms. In order to achieve this goal we
provide a brief survey of commonly used computer vision algorithms that we believe represents a core of
knowledge that all computer vision practitioners should have. This survey is not meant to be an encyclopedic
summary of computer vision techniques as it is impossible to do justice to the scope and depth of the rapidly
expanding field of computer vision.
The arrangement of the book is such that it can serve as a reference for computer vision algorithm developers
in general as well as for algorithm developers using the image algebra C++ object library, iac++.
1
The
techniques and algorithms presented in a given chapter follow a progression of increasing abstractness. Each
technique is introduced by way of a brief discussion of its purpose and methodology. Since the intent of this
text is to train the practitioner in formulating his algorithms and ideas in the succinct mathematical language
provided by image algebra, an effort has been made to provide the precise mathematical formulation of each
methodology. Thus, we suspect that practicing engineers and scientists will find this presentation somewhat
more practical and perhaps a bit less esoteric than those found in research publications or various textbooks
paraphrasing these publications.
1
The iac++ library supports the use of image algebra in the C++ programming language and is available for
anonymous ftp from ftp://ftp.cis.ufl.edu/pub/src/ia/.
Chapter 1 provides a short introduction to field of image algebra. Chapters 2-11 are devoted to particular
techniques commonly used in computer vision algorithm development, ranging from early processing
techniques to such higher level topics as image descriptors and artificial neural networks. Although the
chapters on techniques are most naturally studied in succession, they are not tightly interdependent and can be
studied according to the reader’s particular interest. In the Appendix we present iac++ computer programs
of some of the techniques surveyed in this book. These programs reflect the image algebra pseudocode
presented in the chapters and serve as examples of how image algebra pseudocode can be converted into
efficient computer programs.
