Explore MATLAB source code curated for "纹理图像分割" with clean implementations, documentation, and examples.
Implementation of texture image segmentation based on Gray-Level Co-occurrence Matrix (GLCM) feature extraction and K-Means clustering algorithm using MATLAB
A custom-developed wavelet-based texture segmentation algorithm that performs three-level wavelet decomposition, clusters coefficients at each level, and uses clustering results to guide subsequent level classification, demonstrating excellent segmentation performance with integration of image processing techniques for enhanced results.
MATLAB source code for texture image segmentation implementing wavelet transform coefficient extraction with algorithm implementation details
Comprehensive thesis and implementation code for texture image segmentation - valuable resource for graduation projects featuring complete algorithmic approaches and practical code examples.
Texture Segmentation Implementation with Gabor Filters - Includes PDF documentation and MATLAB M-files for practical implementation
This source code implements Curvelet feature extraction from both color and grayscale images, designed for subsequent texture image segmentation tasks. The implementation includes multi-scale directional analysis using Fast Discrete Curvelet Transform (FDCT) via wrapping.
MATLAB-based texture image segmentation program implementing Gaussian filtering for noise reduction, followed by K-means clustering for region identification, with segmented areas visualized using boundary lines. Complete package includes M-files, test images, PDF documentation, PowerPoint presentation, and Word document for comprehensive understanding.