DocumentCode
3301305
Title
Improved image segmentation method based on optimized threshold using Genetic Algorithm
Author
Zhao, Xin ; Lee, Myung-Eun ; Kim, Soo-Hyung
Author_Institution
Chonnam Nat. Univ., Gwangju
fYear
2008
fDate
March 31 2008-April 4 2008
Firstpage
921
Lastpage
922
Abstract
In image segmentation, threshold segmentation is becoming more and more widely used because of its simplicity and efficiency. In this paper, an improved image segmentation method based on optimized threshold using genetic algorithm is proposed. Compared with the traditional threshold segmentation methods, this method has advantages that it can nicely segment the thin and it can efficiently reduce calculation time and it has good capability and stabilization nature. The results show that using this proposed method can obtain satisfactory segmentation effect.
Keywords
genetic algorithms; image segmentation; genetic algorithm; image segmentation; optimized threshold; threshold segmentation; Biological cells; Entropy; Genetic algorithms; Genetic mutations; Image segmentation; Iterative algorithms; Iterative methods; Optimization methods; Random number generation; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Systems and Applications, 2008. AICCSA 2008. IEEE/ACS International Conference on
Conference_Location
Doha
Print_ISBN
978-1-4244-1967-8
Electronic_ISBN
978-1-4244-1968-5
Type
conf
DOI
10.1109/AICCSA.2008.4493645
Filename
4493645
Link To Document