This book introduces the area of image processing and data-parallel processing. It covers a number of standard algorithms in image processing and describes their parallel implementation. The programming language chosen for all examples is a structured parallel programming language which is ideal for educational purposes. It has a number of advantages over C, and since all image processing tasks are inherently parallel, using a parallel language for presentation actually simplifies the subject matter. This results in shorter source codes and a better understanding. Sample programs and a free compiler are available on an accompanying Web site.

This volume deals with the following topics: 2-D, 3-D automata and grammars, parallel architecture for image processing, parallel digital geometry algorithms, data allocation strategies for parallel image processing algorithms, complexity analysis of parallel image operators. The contributions are written by leading experts in the fields of models, algorithms and architectures for parallel image processing.

This volume deals with the following topics: 2-D, 3-D automata and grammars, parallel architecture for image processing, parallel digital geometry algorithms, data allocation strategies for parallel image processing algorithms, complexity analysis of parallel image operators. The contributions are written by leading experts in the fields of models, algorithms and architectures for parallel image processing.

This review volume contains a selection of papers by leading experts in the areas of Parallel Image Analysis, 2-D, 3-D Grammars and Automata and Neural Nets and Learning.

This book describes the methods and algorithms for image pre-processing and recognition. These methods are based on a parallel shift technology of the imaging copy, as well as simple mathematical operations to allow the generation of a minimum set of features to describe and recognize the image. This book also describes the theoretical foundations of parallel shift technology and pattern recognition. Based on these methods and theories, this book is intended to help researchers with artificial intelligence systems design, robotics, and developing software and hardware applications.

This book develops the mathematical foundation of modern image processing and low-level computer vision, bridging contemporary mathematics with state-of-the-art methodologies in modern image processing, whilst organizing contemporary literature into a coherent and logical structure. The authors have integrated the diversity of modern image processing approaches by revealing the few common threads that connect them to Fourier and spectral analysis, the machinery that image processing has been traditionally built on. The text is systematic and well organized: the geometric, functional, and atomic structures of images are investigated, before moving to a rigorous development and analysis of several image processors. The book is comprehensive and integrative, covering the four most powerful classes of mathematical tools in contemporary image analysis and processing while exploring their intrinsic connections and integration. The material is balanced in theory and computation, following a solid theoretical analysis of model building and performance with computational implementation and numerical examples.

This volume constitutes the refereed proceedings of the 11th International Workshop on Combinatorial Image Analysis, IWCIA 2006, held in Berlin, June 2006. The book presents 34 revised full papers together with two invited papers, covering topics including combinatorial image analysis; grammars and models for analysis and recognition of scenes and images; combinatorial topology and geometry for images; digital geometry of curves and surfaces; algebraic approaches to image processing, and more.