Explore MATLAB source code curated for "纹理" with clean implementations, documentation, and examples.
Perform 3D reconstruction from multiple images by obtaining camera intrinsic parameters through calibration toolbox, followed by texture mapping for realistic visualization.
A MATLAB-based implementation for extracting texture features from digital images with code-level algorithm details
A simple and classic approach for image texture classification using Local Binary Pattern (LBP) algorithm with practical code implementation insights
Texture segmentation for images, suitable for image texture analysis and feature classification, featuring MATLAB-based implementation approaches and algorithm descriptions.
Morphological Component Analysis separates images into texture and smooth components with directly executable implementation
Object tracking program code based on fusion of texture and edge orientation features, developed within the Mean Shift framework with kernel density estimation implementation
Morphological Component Analysis (MCA) is an image processing method that separates images into texture and piecewise-smooth components by leveraging morphological differences in signal constituents. The algorithm typically employs sparse representation with morphological dictionaries like curvelets for textures and wavelets for cartoon parts, achieving separation through optimization techniques such as basis pursuit or iterative thresholding.
Image retrieval system implementation leveraging color histograms and texture analysis algorithms
MATLAB code for Gabor filter implementation, designed for extracting image texture features at various orientations and scales, with detailed algorithm explanation and function descriptions.
MATLAB-based image retrieval system utilizing color moments and texture features, complete with integrated image database and implementation code