Extraction Methods for Gray-Level Co-occurrence Matrix and Gray-Level Gradient Co-occurrence Matrix
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Resource Overview
Gray-Level Co-occurrence Matrix (GLCM) and Gray-Level Gradient Co-occurrence Matrix (GLGCM) extraction methods are significant texture feature extraction techniques implemented using MATLAB for image processing applications.
Detailed Documentation
Gray-Level Co-occurrence Matrix (GLCM) and Gray-Level Gradient Co-occurrence Matrix (GLGCM) are essential methods for extracting texture features from images. The GLCM is generated by calculating the frequency of occurrence of pixel pairs with specific gray-level values within an image, while the GLGCM is derived by computing gradients between different pixel gray-level values. These feature extraction methods find extensive applications in image processing and computer vision domains. Implementing these techniques in MATLAB enables efficient and accurate image processing through built-in functions like graycomatrix() for GLCM calculation and custom algorithms for gradient-based matrix generation. The implementation typically involves specifying parameters such as distance and orientation for pixel pair analysis, followed by feature derivation using statistical measures like contrast, correlation, energy, and homogeneity.
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