Gray-Level Co-occurrence Matrix (GLCM) Implementation Code in MATLAB

The following is the MATLAB implementation code for calculating Gray-Level Co-occurrence Matrix (GLCM). GLCM is a fundamental method for computing texture features in grayscale images. This algorithm determines image texture characteristics by analyzing the spatial relationships and correlations between pixel pairs. GLCM serves as a powerful tool widely used in digital image processing applications. Our MATLAB program accepts grayscale images as input and outputs the computed GLCM matrix with configurable parameters. The implementation includes key features such as: 1. Distance and orientation parameter customization for pixel pair analysis 2. Automatic image quantization to reduce gray levels for computational efficiency 3. Matrix normalization for consistent feature extraction 4. Support for multiple directions (0°, 45°, 90°, 135°) to capture comprehensive texture information The core algorithm involves creating a 2D histogram that counts how frequently pairs of pixels with specific gray-level values occur in the image at a given spatial relationship. The program utilizes MATLAB's matrix operations for efficient computation and includes functions for preprocessing, GLCM calculation, and subsequent texture feature derivation.