The Second Edition of the best-selling Handbook of Computer Vision Algorithms in Image Algebra, continues to provide an outstanding introduction to Image Algebra. It describes more than 80 fundamental computer vision techniques and introduces the portable iac++ library, which supports image algebra programming in the C++ language. Revisions to the first edition include two new chapters on compression techniques and on geometric manipulation/spatial transformation and the addition of exercises to each chapter.
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.