DocumentCode :
2252011
Title :
Painting algorithms for fuzzy classification
Author :
Gómez, Daniel ; Montero, Javier ; Yáñez, Javier ; Poidomani, Carmelo
Author_Institution :
Dept. of Stat. & Oper. Res., Complutense Univ. of Madrid, Spain
Volume :
1
fYear :
2004
fDate :
25-29 July 2004
Firstpage :
127
Abstract :
Land cover analysis by means of remotely sensing images quite often suggests the existence of fuzzy classes, where no clear borders or particular shapes appear. In this paper we present an image classification aid algorithm which shows as its main output a processed image where each pixel is being colored according to the degree of similitude to their respective surrounding pixels. Such a processed image is therefore suggesting possible classes, to be implemented in a more sophisticated image classification process. A key underlying argument for this approach is the relevance of painting techniques in order to help decision makers to understand complex information relative to fuzzy image classification.
Keywords :
fuzzy set theory; image classification; painting; remote sensing; fuzzy image classification; image classification aid algorithm; land cover analysis; painting algorithms; remotely sensing images; Classification algorithms; Computer science; Image analysis; Image classification; Mathematics; Painting; Pixel; Remote sensing; Shape; Statistical analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on
ISSN :
1098-7584
Print_ISBN :
0-7803-8353-2
Type :
conf
DOI :
10.1109/FUZZY.2004.1375701
Filename :
1375701
Link To Document :
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