MATLAB Toolbox for Level Set-Based Image Segmentation

This document introduces a specialized MATLAB toolbox designed for image segmentation, known as the Level Set Image Segmentation Toolbox. The toolkit facilitates image segmentation tasks by implementing level set methods that partition images into distinct regions through evolving contours. Key functions include contour initialization, partial differential equation (PDE) solvers for curve evolution, and energy minimization algorithms. The toolbox provides user-friendly interfaces for parameter configuration, visualization tools for tracking contour evolution, and performance metrics for segmentation evaluation. Researchers can leverage built-in implementations of classic level set variants (e.g., Chan-Vese model) and extend functionality through modular code architecture. Typical workflow involves: 1) Loading medical/natural images via imread(), 2) Initializing contours using initializeContour() function, 3) Configuring evolution parameters like timestep and curvature weight, 4) Running iterative evolution through solveLevelSetPDE(). This toolkit enables deeper analysis of image regions and supports applications in computer vision research, medical imaging, and industrial inspection systems.