Multiple Implementations of Snake Algorithm with MATLAB Examples

This resource package contains eight distinct MATLAB M-files showcasing practical implementations of the snake algorithm (active contour model). The collection includes specialized examples such as "ballon.m" which employs the snake algorithm for precise balloon image segmentation through energy minimization techniques, and "distance.m" that calculates contour-to-edge map distances using gradient vector flow computations. Each M-file implements key snake algorithm components including energy function formulation, contour initialization methods, and iterative convergence procedures. The implementations demonstrate how external energy terms can be tailored for specific applications - balloon inflation forces for region expansion in "ballon.m", and edge-based attraction forces in distance measurement scenarios. Beyond these examples, the snake algorithm proves valuable for various computer vision tasks including object tracking through temporal contour propagation, boundary detection using gradient-based energy minimization, and medical image segmentation. These MATLAB implementations provide practical insights into parameter tuning, convergence criteria settings, and computational efficiency optimization, making them valuable learning resources for image processing professionals and students developing contour-based segmentation solutions.