DocumentCode :
2963620
Title :
A hierarchical genetic algorithm based approach for image segmentation
Author :
Lai, Chih-Chin ; Chang, Chuan-Yu
Author_Institution :
Dept. of Inf. Manage., Shu-Te Univ., Kaohsiung, Taiwan
Volume :
2
fYear :
2004
fDate :
2004
Firstpage :
1284
Abstract :
Image segmentation denotes a process by which an image is partitioned into non-intersecting regions and each region is homogeneous. Many approaches have been proposed for the monochrome image segmentation. Among these approaches, the clustering methods have been extensively investigated and used. In this paper, a clustering based approach using hierarchical genetic algorithm is proposed to tackle the problem of image segmentation. The main advantage of the proposed approach is that it can simultaneously estimate a proper number of regions and then partition the image into several homogeneous regions. The simulation results indicate that the proposed approach can produce more continuous and smoother images in comparison with two existing methods.
Keywords :
genetic algorithms; image segmentation; clustering methods; hierarchical genetic algorithm; image segmentation; Biological cells; Clustering methods; Genetic algorithms; Image processing; Image segmentation; Information management; Noise reduction; Pixel; Robustness; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Networking, Sensing and Control, 2004 IEEE International Conference on
ISSN :
1810-7869
Print_ISBN :
0-7803-8193-9
Type :
conf
DOI :
10.1109/ICNSC.2004.1297132
Filename :
1297132
Link To Document :
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