Grey Level Co-occurrence Matrix (GLCM) Based Second Order Statistics for Image Texture Analysis
Abdul Rasak Zubair, Oluwaseun Adewunmi Alo

TL;DR
This paper analyzes image textures using GLCM and GLDV, computing second order statistics to differentiate between smooth and rough images and exploring directional variations and correlations among features.
Contribution
It provides a detailed analysis of second order texture features from GLCM and GLDV across multiple directions, highlighting their relationships and variations in image smoothness.
Findings
Smooth images have lower Contrast and higher Probability of same-range differences.
Significant correlations exist between contrast and other second order statistics.
Directional differences affect the degree of smoothness or roughness in images.
Abstract
Grey Level Co-occurrence Matrix and Grey Level Difference Vector are described and computed for twenty four 128 x 128 x 3 test images along horizontal, vertical and diagonal directions. Second order image statistics such as Contrast, Dissimilarity, Homogeneity (Inverse Difference Moment), Angular Second Moment, Energy, Maximum Probability, Entropy, Mean, Standard Deviation and Correlation are computed and studied. Grey Level Co-occurrence Matrix (GLCM) and Grey Level Difference Vector (GLDV) are described and computed for twenty four 128 x 128 x 3 test images along horizontal, vertical and diagonal directions. Second order image statistics such as Contrast, Dissimilarity, Homogeneity (Inverse Difference Moment), Angular Second Moment (ASM), Energy, Maximum Probability, Entropy, Mean, Standard Deviation and Correlation are computed and studied. The results show that smooth images have…
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Taxonomy
TopicsMedical Image Segmentation Techniques · Image Retrieval and Classification Techniques · Advanced Image Fusion Techniques
