Adaptive Diffusion Flow Active Contours for Image Segmentation in MATLAB

This paper presents MATLAB source code and examples for adaptive diffusion flow active contours applied to image segmentation. GVF remains a valid external force for active contours, though there exists potential for algorithmic enhancements. Please note that the project files section contains a complete listing of all source code files included in this distribution. Carefully review the file descriptions to ensure they meet your specific implementation requirements. The adaptive diffusion flow active contours technique represents a powerful approach for image segmentation that automatically identifies and separates distinct objects within images. This method operates by classifying image pixels into two categories: foreground and background, achieving segmentation through sophisticated diffusion processes. The implementation includes optimized numerical schemes for solving partial differential equations governing the contour evolution. Key functions handle diffusion coefficient adaptation and boundary condition management. This technique finds applications across various domains including medical image processing and computer vision systems. However, GVF as an external force for active contours still warrants improvement. Current research focuses on developing more effective external forces to enhance contour performance and segmentation accuracy. This project provides working MATLAB code with modular architecture, featuring core functions for force calculation, contour initialization, and iterative refinement. The codebase serves as a foundation for researchers to further explore and advance this robust segmentation methodology through customizable parameters and extendable force field implementations.