Gray-Level Co-occurrence Matrix Texture Calculation Method

The classic Gray-Level Co-occurrence Matrix (GLCM) texture calculation method is a widely used technique in image processing for analyzing texture features and identifying different objects or scenes. This method is based on the gray-level co-occurrence matrix, which calculates the probability of co-occurrence of pixel intensities to describe texture characteristics in images. Implementing this method on the MATLAB platform offers significant convenience, as MATLAB provides numerous built-in functions and toolboxes specifically designed for image processing. Key functions include: - graycomatrix(): Computes the gray-level co-occurrence matrix from an image - graycoprops(): Extracts texture properties from the GLCM (contrast, correlation, energy, homogeneity) - Image Processing Toolbox: Offers comprehensive support for image analysis operations The algorithm implementation typically involves: 1. Image preprocessing and grayscale conversion 2. Defining displacement vectors and quantization levels 3. Calculating co-occurrence matrices for different orientations 4. Extracting statistical texture features from the matrices Using MATLAB for GLCM texture calculation enables users to efficiently analyze image data through streamlined code implementation, automated parameter optimization, and comprehensive visualization capabilities. The platform's matrix-based computation environment significantly simplifies the mathematical operations required for texture feature extraction, making it ideal for both research and practical applications in computer vision and pattern recognition.