About this book
The book presents findings, views and ideas on what exact problems of image processing, pattern recognition and generation can be efficiently solved by cellular automata architectures. This volume provides a convenient collection in this area, in which publications are otherwise widely scattered throughout the literature. The topics covered include image compression and resizing; skeletonization, erosion and dilation; convex hull computation, edge detection and segmentation; forgery detection and content based retrieval; and pattern generation.
The book advances the theory of image processing, pattern recognition and generation as well as the design of efficient algorithms and hardware for parallel image processing and analysis. It is aimed at computer scientists, software programmers, electronic engineers, mathematicians and physicists, and at everyone who studies or develops cellular automaton algorithms and tools for image processing and analysis, or develops novel architectures and implementations of massive parallel computing devices.
The book will provide attractive reading for a general audience because it has do-it-yourself appeal: all the computer experiments presented within it can be implemented with minimal knowledge of programming. The simplicity yet substantial functionality of the cellular automaton approach, and the transparency of the algorithms proposed, makes the text ideal supplementary reading for courses on image processing, parallel computing, automata theory and applications.
Editors and affiliations
- Book Title Cellular Automata in Image Processing and Geometry
- Series Title Emergence, Complexity and Computation
- Series Abbreviated Title Emergence, Complexity, Computation
- DOI https://doi.org/10.1007/978-3-319-06431-4
- Copyright Information Springer International Publishing Switzerland 2014
- Publisher Name Springer, Cham
- eBook Packages Engineering Engineering (R0)
- Hardcover ISBN 978-3-319-06430-7
- Softcover ISBN 978-3-319-35632-7
- eBook ISBN 978-3-319-06431-4
- Series ISSN 2194-7287
- Series E-ISSN 2194-7295
- Edition Number 1
- Number of Pages XVI, 304
- Number of Illustrations 115 b/w illustrations, 49 illustrations in colour
Image Processing and Computer Vision
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