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Fuzzy sets, near sets, and rough sets are useful and important stepping stones in a variety of approaches to image analysis. Emphasizing the utility of fuzzy, near, and rough sets in image analysis, this title introduces the fundamentals and applications in rough fuzzy image analysis.
Based on the author¿s recent research and course at Carnegie Mellon University, this book shows how to integrate image processing, geometric modeling, and mesh generation with the finite element method to solve problems in computational biology, medicine, materials science, and engineering. The text explains the fundamentals of medical imaging, image processing, computational geometry, mesh generation, visualization, and finite element analysis. It also explores novel and advanced applications in computational biology, medicine, materials science, and other engineering areas.
Edited by two leading researchers, this volume reflects the diversity and richness of rough fuzzy image analysis. It explains how fuzzy, near, and rough sets provide the basis for stages of pictorial pattern recognition. It also explains hybrid approaches in image analysis, and tolerance spaces and a perceptual systems approach to image analysis.
Helping readers master digital imaging, this text presents a unified theoretical basis for understanding and designing methods of imaging and image processing. Designed for newcomers to imaging science and engineering, the book covers the subject in its entirety, from image formation to image perfecting. The author avoids using heavy mathematics
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