DocumentCode :
2762978
Title :
A genetic algorithm based method to improve image segmentation
Author :
Visa, Ari
Author_Institution :
Dept. of Inf. Sci., Lappeenranta Univ. of Technol., Finland
Volume :
2
fYear :
1998
fDate :
16-20 Aug 1998
Firstpage :
1015
Abstract :
Segmentation of textured images is becoming more and more important in applications, as quality control or remote sensing. Segmentation of textured images is demanding. A new genetic algorithm based method to post-process segmented texture images is presented. A genetic algorithm is used to extract web-like rules from segmented texture images. These rules are checked and they are used in post-processing to improve the segmentation. An unsupervised image segmentation and definition of classes by class prototypes are assumed. Some preliminary results are presented
Keywords :
genetic algorithms; image segmentation; image texture; genetic algorithm; quality control; remote sensing; textured images; unsupervised image segmentation; web-like rule extraction; Application software; Genetic algorithms; Image processing; Image segmentation; Information science; Prototypes; Quality control; Relaxation methods; Remote sensing; Stochastic resonance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
Conference_Location :
Brisbane, Qld.
ISSN :
1051-4651
Print_ISBN :
0-8186-8512-3
Type :
conf
DOI :
10.1109/ICPR.1998.711861
Filename :
711861
Link To Document :
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