Common MATLAB Image Region Growing Implementation

In image processing, region growing is a fundamental segmentation technique. This method starts from a given seed point and expands to neighboring pixels according to defined threshold criteria, eventually forming a complete homogeneous region. The implementation requires careful consideration of parameters such as growth rate, connectivity (4-connected or 8-connected), and stopping conditions. In MATLAB, this region growing program typically utilizes queue-based or recursive algorithms to systematically examine adjacent pixels. Key functions often include pixel intensity comparison against thresholds, neighborhood connectivity checks, and region boundary management. The algorithm commonly employs while-loops to process candidate pixels and array operations for efficient memory handling. The program's flexibility allows users to customize parameters like similarity thresholds (absolute intensity difference or statistical measures) and connectivity patterns. This adaptability enables various segmentation outcomes, making it suitable for diverse image processing applications ranging from medical imaging to industrial inspection. Users can modify the seed selection strategy and termination conditions to achieve specific segmentation goals.