GVF Snake: Gradient Vector Flow Active Contour Algorithm Implementation

A highly practical GVF Snake program serves as an excellent learning resource for beginners to study code implementation and understand the significance and processing steps of the GVF Snake algorithm. GVF Snake is an active contour algorithm based on Gradient Vector Flow (GVF), widely applied in image segmentation. The primary objective is to segment regions of interest from images. GVF represents a fundamental technique in image processing and computer vision that achieves segmentation by computing gradient vector fields of images. In the GVF Snake program implementation, this technique automatically segments objects within images and generates corresponding contours through iterative energy minimization. The algorithm typically involves initialization of snake points, computation of GVF field using partial differential equations, and iterative deformation toward object boundaries. Key functions include gaussian smoothing for noise reduction, gradient calculation using Sobel or similar operators, and solving the GVF diffusion equations through finite difference methods. By studying this codebase, beginners can deeply understand GVF Snake's algorithmic principles, including energy functional formulation and numerical implementation approaches for solving image segmentation challenges. The implementation demonstrates practical considerations such as parameter tuning for elasticity and stiffness coefficients, convergence criteria, and boundary handling mechanisms.