Feature Extraction Based on Image Gray-Level Co-occurrence Matrix
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Resource Overview
Code implementation for feature extraction using image gray-level co-occurrence matrix, supporting feature calculation in four directions: 0°, 45°, 90°, and 135°, with optional distance parameter configuration.
Detailed Documentation
This implementation enables feature extraction from images using gray-level co-occurrence matrix (GLCM) analysis. The algorithm computes texture features across four directional orientations: 0°, 45°, 90°, and 135°. Key programming components include matrix initialization for each direction, pixel pair counting with configurable distance parameters, and normalization of co-occurrence probabilities. The feature extraction module typically calculates standard texture descriptors such as contrast, correlation, energy, and homogeneity through mathematical operations on the normalized GLCM. The implementation allows adjustable distance parameters (default d=1) for flexible texture analysis at different spatial relationships.
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