Loop-free snakes for image segmentation
L. Ji, Hong Yan · 2003
Snakes are an effective approach to image segmentation. However self-looping is a very common problem that makes snakes fail to work well in certain circumstances. In order to achieve robust segmentation, this paper introduces the loop-free snakes based on an attractable active contour model that overcomes several problems of conventional snake model while retaining all properties associated with it. The proposed method can quickly and efficiently remove all loops during the evolution of snake deformation and can be less sensitive to its parameter setting and flow into more complicated contours such as long tube shapes, sharp corners, deep concave/convex shapes. Hence the new method extends the topologic flexibility and adaptability of snakes. Experiments have been conducted to segment real images with encouraging results.