Graphcut Algorithm Source Code for Image Segmentation

This is a source code implementation of the Graphcut algorithm for image segmentation in the field of image processing, developed using MATLAB. The Graphcut algorithm is a widely-used image segmentation method that partitions images into distinct regions for subsequent processing and analysis. This implementation provides the complete source code, demonstrating key components including graph construction with terminal nodes (source/sink), neighborhood connectivity via adjacency matrices, and energy function minimization using max-flow/min-cut algorithms. The MATLAB implementation offers flexibility through customizable parameters such as regional term weights (data cost) and boundary term coefficients (smoothness cost), allowing users to adapt the algorithm to specific requirements. Key functions include graph initialization with intensity-based penalties, iterative optimization using Boykov-Kolmogorov max-flow computation, and post-processing for label assignment. Suitable for both academic research and practical applications, this implementation serves as an educational resource for understanding graph-based segmentation while providing a foundation for developing customized variants. The code structure facilitates modifications including alternative energy functions, different connectivity patterns, and integration with pre-processing filters.