Fuzzy Rule-Based Edge Detection Using Multiscale Edge Images

Kaoru ARAKAWA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E83-A   No.2   pp.291-300
Publication Date: 2000/02/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Intelligent Signal and Image Processing)
Category: 
Keyword: 
edge detection,  fuzzy rules,  image processing,  multiscale analyses,  optimization,  

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Summary: 
Fuzzy rule-based edge detection using multiscale edge images is proposed. In this method, the edge image is obtained by fuzzy approximate reasoning from multiscale edge images which are obtained by derivative operators with various window sizes. The effect of utilizing multiscale edge images for edge detection is already known, but how to design the rules for deciding edges from multiscale edge images is not clarified yet. In this paper, the rules are represented in a fuzzy style, since edges are usually defined ambiguously, and the fuzzy rules are designed optimally by a training method. Here, the fuzzy approximate reasoning is expressed as a nonlinear function of the multiscale edge image data, and the nonlinear function is optimized so that the mean square error of the edge detection be the minimum. Computer simulations verify its high performance for actual images.