Title :
A Multilevel Thresholding Method Based on Cross Entropy and Genetic Algorithms
Author :
Huang, Shu-Chien
Author_Institution :
Dept. of Comput. Sci., Nat. PingTung Univ. of Educ., Pingtung, Taiwan
Abstract :
Threshold selection is one of the most important issues in image processing. In this paper, a general technique for multilevel thresholding based on cross entropy is proposed. Then, a genetic algorithm is designed especially for searching for the near-optimal or optimal thresholds. The effectiveness and efficiency of the proposed method is demonstrated by using well-known images.
Keywords :
genetic algorithms; image segmentation; cross entropy methods; genetic algorithms; multilevel thresholding method; optimal thresholds; Algorithm design and analysis; Ant colony optimization; Biological cells; Computer science; Computer science education; Entropy; Genetic algorithms; Histograms; Image processing; Image segmentation;
Conference_Titel :
Innovative Computing, Information and Control (ICICIC), 2009 Fourth International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-4244-5543-0
DOI :
10.1109/ICICIC.2009.29
