DocumentCode :
2926389
Title :
One-dimensional Grey-level Co-occurrence Matrices for texture classification
Author :
Tou, Jing Yi ; Tay, Yong Haur ; Lau, Phooi Yee
Author_Institution :
Comput. Vision & Intell. Syst. (CVIS) Group, Univ. Tunku Abdul Rahman, Kampar
Volume :
3
fYear :
2008
fDate :
26-28 Aug. 2008
Firstpage :
1
Lastpage :
6
Abstract :
The grey-level co-occurrence matrices (GLCM) has been widely used for various texture analysis implementations and has provided satisfying results. The conventional GLCM method is two dimensional as it focus on the co-occurrence of the specific pixel pairs. The one-dimensional GLCM reduces the matrices to a single dimension by focusing only on the differences of the grey level between pixel pairs. The experiment results on 32 Brodatz textures shows that in a same setting, the one-dimensional GLCM achieved a recognition rate of 83.01% while the conventional GLCM achieved a recognition rate of 81.35%. The results show that the one-dimensional GLCM can perform as good as the conventional GLCM but with fewer computations involved.
Keywords :
image classification; image texture; matrix algebra; image texture classification; one-dimensional grey-level co-occurrence matrix; Artificial intelligence; Computer vision; Face detection; Face recognition; Feature extraction; Intelligent robots; Intelligent systems; Pattern recognition; Telecommunications; Turing machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology, 2008. ITSim 2008. International Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-2327-9
Electronic_ISBN :
978-1-4244-2328-6
Type :
conf
DOI :
10.1109/ITSIM.2008.4631992
Filename :
4631992
Link To Document :
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