DocumentCode
2486467
Title
The image segmentation algorithm based on 2-D maximum entropy
Author
Liu, Binghan ; Guo, Mingshan ; Wang, Weizhi
Author_Institution
Coll. of Math. & Comput. Sci., Univ. of Fuzhou, Fuzhou
fYear
2008
fDate
25-27 June 2008
Firstpage
3628
Lastpage
3632
Abstract
2D maximum entropy algorithm is of quite good effect in image segmentation, but it requires long time on the complex calculation. Considering CGApsilas (chaos genetic algorithm) ability to retain the species diversity and great astringencypsila a new 2-D maximum entropy method based on CGA was put forward. It has been proved that the new algorithm is of better capacity to search for the best , performs more steadily and results in better segmentation effect.
Keywords
genetic algorithms; image segmentation; maximum entropy methods; 2D maximum entropy; chaos genetic algorithm; image segmentation; Automation; Chaos; Diversity reception; Educational institutions; Entropy; Genetic algorithms; Histograms; Image segmentation; Intelligent control; Mathematics; 2-D maximum entropy; chaos genetic algorithm; image segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location
Chongqing
Print_ISBN
978-1-4244-2113-8
Electronic_ISBN
978-1-4244-2114-5
Type
conf
DOI
10.1109/WCICA.2008.4593503
Filename
4593503
Link To Document