Explore MATLAB source code curated for "灰度共生矩阵" with clean implementations, documentation, and examples.
Implementation of texture image classification using Gray-Level Co-occurrence Matrix (GLCM) feature extraction and k-Nearest Neighbor (k-NN) algorithm. The creat_apprentissage function handles training sample preparation, cooccurence performs GLCM-based feature extraction, knn implements the classification algorithm, and classif executes the final texture image categorization.
This program implements an image texture feature extraction algorithm using Gray-Level Co-occurrence Matrix (GLCM), calculating GLCM across four distinct directions to derive texture feature vectors, followed by averaging to significantly enhance computational efficiency
A practical MATLAB program for computing the gray-level co-occurrence matrix of images, featuring optimized code structure and texture analysis capabilities
Learn how to implement gray-level co-occurrence matrix (GLCM) and extract its statistical features using MATLAB, including detailed code implementation and function explanations for texture analysis applications.
Comprehensive GLCM resources including MATLAB code for generating co-occurrence matrices, the missing graycomatrix.m file from MATLAB 7 toolbox, and a feature extraction program that calculates over 20 texture features from GLCM. The implementation demonstrates practical approaches for texture analysis using statistical properties derived from pixel relationships.
A comprehensive implementation for computing gray-level co-occurrence matrices, featuring modular subroutines suitable for texture analysis applications
Classic Gray-Level Co-occurrence Matrix texture calculation method implemented on the MATLAB platform with code implementation details
MATLAB-based texture feature extraction using gray-level co-occurrence matrix for image pattern analysis
MATLAB program code for calculating Gray-Level Co-occurrence Matrix with detailed algorithm implementation and texture feature extraction capabilities
Texture feature extraction based on Gray-Level Co-occurrence Matrix (GLCM). Key feature parameters include: entropy, energy, contrast, and homogeneity.