Interactive Image Segmentation Based on Maximum Similarity Region Merging

This program implements an interactive image segmentation algorithm designed specifically for region merging based on maximum similarity criteria. The core functionality enables users to partition images into distinct regions and perform merging operations to achieve optimal segmentation results. Key algorithmic components include: - Region adjacency graph construction for efficient neighbor relationship management - Similarity metric calculation using combined color and texture features - Priority queue implementation for always merging the most similar regions first - Interactive seed point selection with real-time region growth visualization The code architecture employs efficient data structures to handle large-scale image processing, with modular functions for region initialization, similarity computation, and merge validation. Extensive testing confirms robust performance across various image types and segmentation scenarios. Users can confidently deploy this implementation for reliable image segmentation tasks with guaranteed stability and accuracy.