Title :
The selection of local dynamic threshold based on niched genetic algorithm
Author :
Chen, Xi ; Yang, Jie
Author_Institution :
Wuhan Univ. of Technol., Wuhan
Abstract :
In this paper, one improved algorithm for the selection of local dynamic threshold based on niched genetic algorithm is proposed. With the maximum variance method being used as the fitness evaluation function, the genetic algorithm is designed, putting the image segmentation problem into one of the optimization issue. The optimal threshold is searched from the all segmentation parameter space by experiencing the global exploring ability of the genetic algorithm. Compared with some problems of simple genetic algorithm, these are amended by the niche idea. The results of experiment show that the proposed method has better robust performance.
Keywords :
genetic algorithms; image segmentation; probability; fitness evaluation function; genetic algorithm; image segmentation; local dynamic threshold; maximum variance; optimal threshold; segmentation parameter space; Algorithm design and analysis; Background noise; Entropy; Genetic algorithms; Image segmentation; Notice of Violation; Pattern analysis; Pattern recognition; Real time systems; Wavelet analysis; Image segmentation; genetic algorithm; local dynamic threshold; maximum variance; niche;
Conference_Titel :
Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1065-1
Electronic_ISBN :
978-1-4244-1066-8
DOI :
10.1109/ICWAPR.2007.4421570
