Explore MATLAB source code curated for "区域生长法" with clean implementations, documentation, and examples.
A comprehensive MATLAB implementation of image segmentation based on region growing algorithm, featuring pixel similarity analysis and expandable functionality for preprocessing and postprocessing operations.
This region growing-based program is primarily designed for false alarm elimination and can calculate the area of each connected component in binary images. The implementation utilizes connected component analysis with seed point selection and neighborhood pixel aggregation.
Image segmentation algorithm using region growing method to segment brain MRI images starting from a single seed point with implementation details
Medical image processing implementation featuring two segmentation approaches: region growing-based segmentation and optimal threshold-based segmentation with code-level algorithm explanations
Enhanced implementation of the region growing method from Gonzalez's "Digital Image Processing" featuring three distinct seed point selection approaches: grayscale-based selection, position-based selection, and interactive single-seed selection with corresponding code implementation strategies.
This program implements a GUI interface for traffic sign image segmentation, primarily utilizing three segmentation methods: Otsu's method, iterative threshold selection algorithm, and region growing algorithm.
MATLAB code for image segmentation featuring watershed algorithm and region growing methods - thoroughly tested with excellent performance results
A comprehensive MATLAB program implementing the region growing method for image segmentation, featuring seed selection, similarity criteria, and region expansion techniques.
This algorithm converts RGB images to grayscale first, then performs image segmentation using region growing methodology with pixel similarity analysis
This program implements region growing algorithm for image segmentation with four input parameters: 1) x-coordinate of seed point, 2) y-coordinate of seed point, 3) input image for segmentation, 4) threshold value used during region growth. The algorithm uses pixel connectivity and similarity criteria to expand regions from seed points.