Rough Fuzzy Image Analysis: Foundations and Methodologies

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  • Edition: 1st
  • Format: Hardcover
  • Copyright: 2010-05-04
  • Publisher: CRC Press

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Written by international experts in image analysis, this book brings together coverage of the state of the art in rough fuzzy image analysis. It presents the principal, representative methods useful in image analysis and describes the concepts, theories, and algorithms that demonstrate how rough fuzzy can be used in image analysis in real-life applications. Topics covered include clustering using rough approximation, rough entropy, rough fuzzy neural computing, image segmentation quality method, and neuro-fuzzy segmentation. Each chapter contains a tutorial introduction followed by an exhaustive description of the development in each respective area.

Author Biography

Alison Lindsay has been scrapbooking for more than ten years; ever since she realized it was a hobby that allowed her to combine a lifetime of photographs with the crafts she loves. Vacation, heritage and family photographs are her favorite scrapbook subject. Alison has written for craft magazines on cardmaking and scrapbooking, and regularly demonstrates new techniques and products at craft fairs.

Table of Contents

Cantor, Fuzzy, Near, and Rough Sets in Image Analysisp. 1
Rough-Fuzzy Clustering Algorithm for Segmentation of Brain MR Imagesp. 2
Image Thresholding using Generalized Rough Setsp. 3
Mathematical Morphology and Rough Setsp. 4
Rough Hybrid Scheme: An application of breast cancer imagingp. 5
Applications of Fuzzy Rule-based Systems in Medical Image Understandingp. 6
Near Set Evaluation And Recognition (NEAR) Systemp. 7
Perceptual Systems Approach to Measuring Image Resemblancep. 8
From Tolerance Near Sets to Perceptual Image Analysisp. 9
Image Segmentation: A Rough-set Theoretic Approachp. 10
Rough Fuzzy Measures in Image Segmentation and Analysisp. 11
Discovering Image Similarities. Tolerance Near Set Approachp. 12
Indexp. I
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