Image Segmentation Implementation Using Level Set Method

This MATLAB-implemented code performs image segmentation with exceptional performance on images having minimal grayscale differences between background and foreground regions. It utilizes the Chan-Vese (CV) model, which belongs to the active contour model family. The program implements a semi-implicit numerical scheme to solve the variational level set formulation of the CV model, ensuring stable and efficient segmentation results. The implementation features: - Level set function initialization using signed distance functions - Regularization terms for smooth evolution of contours - Energy minimization through gradient descent approaches - Automatic handling of topological changes during contour evolution This code can be extended to other image segmentation tasks such as edge detection and object recognition. Users can modify parameters and optimize the algorithm according to specific image characteristics and application scenarios. The implementation provides a solid foundation for variational image processing techniques.