A Novel Approach to Image Enhancement and Thresholding Based on Fuzzy Theory

Image processing has to deal with many ambiguous situations. Fuzzy set theory is a useful mathematical tool for handling the ambiguity or uncertainty. In order to apply the fuzzy theory, selecting the fuzzy region of membership function is a fundamental and important task. In this paper, a new metho...

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Bibliographic Details
Main Authors: Shi Zhen-gang, Gao Li-qun, Wan Kun
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Entropy
fuzzy enhancement
fuzzy entropy
Fuzzy set theory
Fuzzy sets
Image enhancement
Image processing
membership function
Optimization methods
Particle swarm optimization
particle swarm optimization (PSO)
Probability distribution
Uncertainty
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Summary:Image processing has to deal with many ambiguous situations. Fuzzy set theory is a useful mathematical tool for handling the ambiguity or uncertainty. In order to apply the fuzzy theory, selecting the fuzzy region of membership function is a fundamental and important task. In this paper, a new method of membership function based on fuzzy theory by PSO algorithm optimized was proposed by analyzing the deficiencies of traditional enhancement algorithm. A new entropy definition of a fuzzy set was proposed. The new entropy definition of a fuzzy set was not only related to the membership (fuzzy domain) but also related to the probability distribution (space domain), it can respond to the variety of image input information. In addition, by quoting a novel particle swarm optimization (PSO) algorithm to find the optimization parameters for membership. We have employed the new proposed approach to perform image enhancement and thresholding and obtained satisfactory results.
ISSN:2156-2318
2158-2297
DOI:10.1109/ICIEA.2007.4318801