Advanced gradient segmentation model based on Chan-Vese level set method

In order to increase the speed and precision of image segmentation,proposed a novel gradient advanced segmentation model based on Chan-Vese level set method.First,added an internal energy term in order to counteract the discrepancy of the level set function and the signed distance function during iteration,so eliminated the troublesome re-initialization process.Second,proposed the gradient-advanced term,which could attain the desired boundaries faster than others if there was more than one object in the detection area.Moreover,the gradient-advanced term could also increase the segmentation precision of weak boundaries.A number of experiments prove the validity and robustness of the model in segmenting exact areas and maintaining the stability of evolvement.