Active contour model by kernel-induced distance fitting energy
Xia De-shen · Jisuanji yingyong yanjiu · 2012
This paper proposed a new active contour model based on kernel-induced distance for image segmentation.It introduced a local fitting energy with a kernel-induced distance,which enabled the extraction of accurate local image information.Therefore,this model could be used to segment images with intensity inhomogeneity.In addition,it used the level set regularizing term to avoid expensive reinitialiation of the evolving level set and improved the segmentation speed.Experimental results demonstrate that the proposed algorithm can overcome intensity inhomogeneity,and get the more accurate segmentation result,especially there is about 1.3 to 1.5 times faster than the LBF model.