Classical Region Growing Algorithm

This program implements the classical region growing algorithm for image segmentation and object recognition. The algorithm automatically partitions images into multiple regions, enabling effective identification and isolation of target objects. The implementation incorporates various image processing techniques, including edge detection and color segmentation. Specifically, the algorithm leverages watershed transformation and image clustering techniques, demonstrating excellent performance across different images with vibrant colors, strong contrast, and clear details. The detailed code annotations provide insights into the algorithm's implementation process and underlying principles, covering key aspects such as seed point selection, similarity criteria for region expansion, and stopping conditions. This facilitates better understanding and application of the algorithm for image segmentation and object recognition tasks. The code structure includes modular functions for preprocessing, region growing core logic, and result visualization, making it suitable for both educational and practical implementations.