Practical Active Contour Model Implementation

This MATLAB program provides a robust implementation of active contour models (also known as snakes) designed for versatile applications in image segmentation and boundary detection. The implementation incorporates energy minimization algorithms that allow the contour to evolve and adapt to image features through iterative optimization processes. Key algorithmic features include: - Gradient vector flow (GVF) for improved convergence in concave regions - Customizable internal energy terms controlling contour smoothness and elasticity - External energy functions based on image gradients and user-defined constraints - Interactive parameter tuning for alpha (elasticity), beta (rigidity), and gamma (step size) The code architecture utilizes MATLAB's image processing toolbox for efficient matrix operations and includes visualization functions that display contour evolution in real-time. Users can modify initialization points, adjust convergence criteria, and implement custom energy functions through well-documented interface functions. Designed with accessibility in mind, the program includes example scripts demonstrating basic usage patterns and common parameter configurations. The modular design allows easy integration with existing image processing workflows while maintaining computational efficiency through vectorized operations. Whether for academic research, medical image analysis, or computer vision applications, this implementation provides a foundation for advanced contour modeling with clear documentation and extensible code structure.