Co-Occurrence Matrix-Based Statistical Model for Texture Analysis from Images

Abstract:

Texture surface analysis is very important for machine vision system. We explore Gray Level Co-occurrence Matrix-based 2^nd order statistical features to understand image texture surface. We employed several features on our ground-truth dataset to understand its nature; and later employed it in a building dataset. Based on our experimental results, we can conclude that these image features can be useful for texture analysis and related fields.

• Periodical: Applied Mechanics and Materials (Volume 103)
• Pages: 717-724
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.103.717
• Online since: September 2011
• Authors: Hossain Shahera, Seiichi Serikawa
• Keywords: Co-Occurrence Matrix, Entropy, GLCM, Image Feature, Statistical Model, Texture Analysis

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