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Gray Level Co-Occurrence Matrices: Generalisation and Some New Features

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arxiv 1205.4831 v1 pith:PY4ELE3H submitted 2012-05-22 cs.CV

Bino Sebastian V , A. Unnikrishnan , Kannan Balakrishnan This is my paper · ORCID
classification cs.CV
keywords featuresglcmgrayanalysiscbirco-occurrencediscussedimage
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Gray Level Co-occurrence Matrices (GLCM) are one of the earliest techniques used for image texture analysis. In this paper we defined a new feature called trace extracted from the GLCM and its implications in texture analysis are discussed in the context of Content Based Image Retrieval (CBIR). The theoretical extension of GLCM to n-dimensional gray scale images are also discussed. The results indicate that trace features outperform Haralick features when applied to CBIR.

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Cited by 2 Pith papers

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