Image segmentation based on GVF snake and boundary tracking
Jiang Xiaob · Journal of University of Jinan · 2015
Gradient vector flow active contour method in dealing image segmentation have achieved good results,but it largely depends on the initial contour curve and the long time cost of compute the gradient vector field. A method which is based on GVF Snake model for image segmentation is proposed. The method uses the boundary extraction algorithm for coarse segmentation,to obtain effective information points edges postion,then samples the information points to generate the initial contour. Meanwhile,the Lagrangian method is used to numerically compute the gradient vector field,a termination condition based on distance is given. which can effectively improve the computing speed. Experiments performed on standard test images showed that the method,compared with the traditional,manual method and CV active contour,which effectively improves the degree of automation and guarantees relatively segmentation precision in image segmentation processing.