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