DocumentCode
467003
Title
Maximum Variance Image Segmentation Based on Improved Genetic Algorithm
Author
Wang Chun-mei ; Wang Su-zhen ; Zhang Chong-ming ; Zou Jun-zhong
Author_Institution
East China Univ. of Sci. & Technol., Shanghai
Volume
2
fYear
2007
fDate
July 30 2007-Aug. 1 2007
Firstpage
491
Lastpage
494
Abstract
An image segmentation method based on the OTSU and improved genetic algorithm (GA) is presented. The OTSU is taken as evaluation function and the segmentation problem is turned to the optimization problem. That is, GA efficiently searches the segmentation parameter space in order to obtain the optimal threshold. On the other hand, to overcome some limitation of GA, elite reinsertion is applied. The experimental results indicate that the method can not only obtain a better result, but also shorten the processing time.
Keywords
genetic algorithms; image segmentation; elite reinsertion; genetic algorithm; maximum variance image segmentation; optimal image threshold; optimization; Biological cells; Educational institutions; Genetic algorithms; Histograms; Image edge detection; Image segmentation; Pixel; Software engineering; Space technology; Target recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on
Conference_Location
Qingdao
Print_ISBN
978-0-7695-2909-7
Type
conf
DOI
10.1109/SNPD.2007.252
Filename
4287734
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