An intelligent and attractable active contour model for boundary extraction
L. Ji, Hong Yan · 1999
An intelligent and attractable active contour model for boundary extraction is presented in this paper. The proposed model is capable of driving any initial guess in the area of the evolving estimate towards the desired boundary, working against a constant image background, overcoming spurious edge-points and fitting into the object without any overrun. It is also capable of extracting both concave and convex boundaries while still being capable of bearing subjective boundaries with help of a synthetic convergent criterion and an adaptable interpolation scheme. Using additional two control parameters, it is possible to control the convergent properties of the new model, which provides a high degree of flexibility and adaptability. This robust model has been applied to real images with encouraging results.