Texture Feature Extraction Based on Gray-Level Co-occurrence Matrix

In this approach, we extract texture features from images using the Gray-Level Co-occurrence Matrix (GLCM) method. This technique involves analyzing the image across four directional orientations (typically 0°, 45°, 90°, and 135°) and computing statistical features for each direction. The implementation typically involves creating GLCMs for each orientation using distance and angle parameters, then calculating four key texture features per direction: Contrast, Correlation, Energy, and Homogeneity. Through this process, we obtain a total of sixteen distinct feature values that comprehensively characterize the image's texture properties. These features provide detailed quantitative descriptions of texture patterns, enabling richer information for image analysis applications such as classification, segmentation, and pattern recognition. Key functions in implementation would include graycomatrix() for matrix generation and graycoprops() for feature calculation, with parameters specifying the distance between pixel pairs and the angular relationships.