DocumentCode :
2097404
Title :
Region segmentation using K-mean clustering and genetic algorithms
Author :
Horita, Yuukou ; Murai, Tadahuni ; Miyahara, Makoto
Author_Institution :
Dept. of Electron. & Comput. Sci., Toyama Univ., Japan
Volume :
3
fYear :
1994
fDate :
13-16 Nov 1994
Firstpage :
1016
Abstract :
One of the hard problems in image recognition and understanding is region segmentation. A traditional segmentation method such as clustering is not fully useful for any image, because of the initial values of clusters and the evaluation functions of segmented clusters affect the results of region segmentation. To solve this problem, we introduce the genetic algorithm (GA) for clustering. The experimental result shows the satiable results of region segmentation which have been achieved by applying GA
Keywords :
genetic algorithms; image recognition; image segmentation; K-mean clustering; clustering; genetic algorithm; genetic algorithms; image recognition; region segmentation; Clustering methods; Color; Computer science; Genetic algorithms; Genetic engineering; Genetic mutations; Histograms; Image edge detection; Image recognition; Image segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference
Conference_Location :
Austin, TX
Print_ISBN :
0-8186-6952-7
Type :
conf
DOI :
10.1109/ICIP.1994.413691
Filename :
413691
Link To Document :
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