Region Growing Image Segmentation

The MATLAB region growing image segmentation program implements an image segmentation algorithm that grows regions by searching neighboring pixels from seed points. This algorithm effectively partitions images into distinct regions, enabling extraction of target objects from images. In this implementation, the program first selects a seed point as the starting position, then evaluates neighboring pixels based on predefined criteria (typically intensity similarity and connectivity) to determine if they belong to the same region. Qualifying pixels are progressively added to the current region, continuously expanding the area until no new pixels can be incorporated. The algorithm typically utilizes 4-connected or 8-connected neighborhood searching methods, with pixel similarity thresholds controlling the growth process. Key implementation aspects include: - Seed point selection through manual input or automated detection - Neighborhood exploration using queue or stack data structures - Pixel similarity evaluation using intensity difference thresholds - Region boundary management and termination conditions This approach enables precise image segmentation that can be further enhanced with post-processing techniques such as morphological operations or connectivity analysis for improved results in computer vision applications.