Abstract
A novel region-scalable fitting (RSF) active contour model with symmetric cross entropy (SCE)-based global constraint is proposed to segment various kinds of images. The energy functional is mainly composed of two parts, namely the local and global constraints. The local constraint is the weighted region-scalable fitting term, which computes the local intensity information. The global constraint is constructed by measuring the difference between the intensity distribution of the object image and the intensity distribution of the original image using SCE. Moreover, some regularised terms are incorporated into the energy functional. Experimental results for synthetic and real images show that the proposed model achieves better segmentation performance and is insensitive to initial contour and noise.
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