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