DocumentCode :
480071
Title :
Application of an Improved Genetic Algorithm in Image Segmentation
Author :
Hui, Lei ; Shi, Cheng ; Min-si, Ao ; Yi-qi, Wu
Author_Institution :
Fac. of Mech. & Electron. Inf., China Univ. of Geosci., Wuhan
Volume :
3
fYear :
2008
fDate :
12-14 Dec. 2008
Firstpage :
898
Lastpage :
901
Abstract :
The selection of threshold is critical in image segmentation. Based on genetic algorithm, an improved method for selecting the optimal threshold in image segmentation is proposed. In the computational process, the improved GA adjusts crossover probability and mutation probability automatically according to the variance between the target and background, thus overcoming the problems of poor astringency and premature occurrence in Simple Genetic Algorithm. Moreover, the improved GA is used to find the optimum relation of the evaluation function on the basis of OTSU Principle in the paper. The experimental data demonstrate that this improved GA has a better convergence and stability than the Simple GA.
Keywords :
genetic algorithms; image segmentation; probability; genetic algorithm; image segmentation; optimal threshold; probability; Computer science; Convergence; Equations; Genetic algorithms; Genetic mutations; Geology; Histograms; Image segmentation; Pixel; Stability; image segmentation; improved genetic algorithm; segmentation threshold;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
Type :
conf
DOI :
10.1109/CSSE.2008.794
Filename :
4722487
Link To Document :
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