Image Texture Feature Extraction with MATLAB Implementation

In this documentation, I have developed a MATLAB program designed for extracting texture features from images. This implementation is particularly suitable for image processing applications, enabling enhanced understanding and analysis of visual data. The program employs various texture analysis algorithms including Gray-Level Co-occurrence Matrix (GLCM) features, Local Binary Patterns (LBP), and Gabor filter-based approaches to capture comprehensive texture information from images.

Key implementation details include: preprocessing steps for image normalization, feature extraction functions utilizing MATLAB's Image Processing Toolbox, and output generation of texture descriptors such as contrast, correlation, energy, and homogeneity. The program architecture follows modular design principles with separate functions for different texture analysis methods, allowing for flexible customization and extension.

This development is based on in-depth research and understanding of image processing algorithms and texture feature extraction techniques, ensuring accuracy and effectiveness in feature computation. The code includes error handling for invalid inputs and supports multiple image formats through MATLAB's imread function. I anticipate this program will provide significant convenience and assistance for your image processing workflows, particularly in applications like pattern recognition, medical image analysis, and material classification.