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

2012/05/22 by Bino Sebastian V, Sebastian, Bino, A. Unnikrishnan +4 · 1 citation
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image Retrieval and Classification Techniques #Medical Image Segmentation Techniques #Rough Sets and Fuzzy Logic

paper · pdf · doi:10.48550/arxiv.1205.4831

openalex publication_date 2012/05/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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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