Title :
A Novel Approach to Image Enhancement and Thresholding Based on Fuzzy Theory
Author :
Zhen-Gang, Shi ; Li-Qun, Gao ; Kun, Wan
Author_Institution :
Northeastern Univ., Shenyang
Abstract :
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.
Keywords :
entropy; fuzzy set theory; image enhancement; image segmentation; particle swarm optimisation; entropy definition; fuzzy set theory; image enhancement; image thresholding; mathematical tool; particle swarm optimization; probability distribution; Algorithm design and analysis; Entropy; Fuzzy set theory; Fuzzy sets; Image enhancement; Image processing; Optimization methods; Particle swarm optimization; Probability distribution; Uncertainty; fuzzy enhancement; fuzzy entropy; membership function; particle swarm optimization (PSO);
Conference_Titel :
Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-0737-8
Electronic_ISBN :
978-1-4244-0737-8
DOI :
10.1109/ICIEA.2007.4318801