In this paper, we propose an object(s)-of-interest (OOI) segmentation method for images with inhomogeneous intensities. First, we define a discrimination function for each pixel, labelling whether the pixel belongs to OOI based on the characteristics of OOI. This function is then integrated with image gradient to construct a stopping function in an energy functional. Finally, this energy functional is minimized by means of level set evolution, which guides the motion of the zero level set toward object boundaries. The results demonstrate that our model is effective.
['Yaxin Peng', 'Lili Bao', 'Ling Pi']
Object(s)-of-interest segmentation for images with inhomogeneous intensities based on curve evolution