MATLAB Implementation for Calculating Gray-Level Co-occurrence Matrix (GLCM) of Images

This MATLAB program is designed to calculate the gray-level co-occurrence matrix (GLCM) of images, implementing essential image processing algorithms for texture analysis. The code utilizes MATLAB's built-in functions like graycomatrix() and graycoprops() to efficiently compute spatial relationships between pixel pairs at specified offsets and distances. Through comprehensive analysis of the GLCM, users can extract critical texture features including contrast, correlation, energy, and homogeneity - fundamental parameters for image characterization. These statistical measures are vital for image processing applications such as pattern recognition, image classification, and material identification. The implementation includes configurable parameters for gray-level quantization, displacement vectors, and symmetric matrix handling, ensuring adaptability to various image types. Understanding GLCM computation methodologies and their practical applications provides significant value in computer vision research. This program serves as an effective tool for both academic research and industrial image analysis projects, offering optimized performance and clear documentation for seamless integration into larger image processing workflows.