An Image Segmentation Algorithm Using Region Growing Approach

This article introduces an image segmentation algorithm based on region growing methodology. The algorithm initiates by selecting a single pixel as a seed point, which serves as the starting position for region expansion. Through iterative expansion to adjacent pixels, the algorithm evaluates color similarity between neighboring pixels and the seed point. When the color similarity meets a predefined threshold, the pixel is incorporated into the growing region. Key implementation aspects include: - Seed point selection using intensity-based or user-defined criteria - Similarity measurement typically using Euclidean distance in color space - Connectivity rules (4-connected or 8-connected) governing expansion directions The expansion process continues until no more pixels satisfy the similarity condition, ultimately producing closed contours that delineate segmented regions. This algorithm finds applications in medical image processing, computer vision systems, and other domains requiring precise image partitioning.