Active Contour Model - Snake Model

The Active Contour Model, commonly known as the "Snake Model," is a classic algorithm for image segmentation. It operates by defining a deformable contour that progressively conforms to target edges under the influence of image gradients and internal constraint forces.

Core Concept: The snake contour is formulated as an energy minimization problem, comprising internal energy (controlling curve smoothness) and external energy (attracting the curve to target edges). The algorithm iteratively adjusts contour point positions to minimize the total energy function.

MATLAB Implementation Key Steps: Initialize contour line (e.g., closed polygon around target object) Compute image gradient to create external force field Define energy function weight parameters (elasticity/bending coefficients) Iterative energy minimization using optimization methods (commonly gradient descent) Code implementation typically involves solving Euler-Lagrange equations through finite difference methods, with MATLAB's image processing toolbox providing gradient computation functions like imgradient

Application Scenarios: Particularly effective for medical image segmentation and motion tracking where edges are distinct but noise is prevalent. In MATLAB, implementation can be enhanced using optimization toolbox functions alongside image processing routines, with careful parameter tuning being crucial for segmentation accuracy. Key considerations include balancing internal/external energy weights and selecting appropriate convergence criteria.