A Novel Method with Immune Genetic Algorithm Based on Snakes for Edge Detection of Concave Boundary
Hong Duan, Huang You-rui · 2007
Snake models are extensively used from its debut in image processing and motion tracking, but its poor convergence on concave boundary is a handicap for object location. Although, the GVF snake model shows high performance for this problem, but it suffers from costly computation by virtual of PDE's and another so-called critical point problem for the initial contour selection. So a new method with immune genetic algorithm based on snake for edge detection of concave boundary is proposed. After detecting the edge with snake, the proposed method is used to find out the area of concave boundary. And then the immune genetic algorithm is used to optimize the edge of concave boundary. The proposed algorithm has better segmentation result than basic snake algorithm for edge detection of concave boundary.