DocumentCode :
2144987
Title :
The Classification Study of Texture Image Based on the Rough Set Theory
Author :
Lin, Huang ; Wang, Ji-Yi ; Liu, Shuang
Author_Institution :
Coll. of Math. Inf., Zhejiang Normal Univ., Jinhua, China
fYear :
2010
fDate :
14-16 Aug. 2010
Firstpage :
720
Lastpage :
723
Abstract :
This paper proposes an automatic classification model based on rough set theory for texture image. The features from texture image are extracted by the gray level co-occurrence Matrix (GLCM), then some redundant features of them are reduced under the background of knowledge reduction of rough set theory in order to mine classification rules of texture images. And experiment shows that this model has higher classification accuracy for the automatic classification of decorative stone images.
Keywords :
feature extraction; image classification; image texture; rough set theory; classification rules mining; decorative stone image classification; gray level co-occurrence matrix; knowledge reduction; rough set theory; texture image classification; Accuracy; Classification algorithms; Feature extraction; Rough sets; Testing; Training; GLCM; rough set; texture image;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing (GrC), 2010 IEEE International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-7964-1
Type :
conf
DOI :
10.1109/GrC.2010.33
Filename :
5576051
Link To Document :
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