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One-dimensional Grey-level Co-occurrence Matrices for texture classification
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 matri...
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Main Authors: | , , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
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Summary: | 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. |
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ISSN: | 2155-8973 |
DOI: | 10.1109/ITSIM.2008.4631992 |