Active contours with selective local or global segmentation property for multiobject image

Abstract

In this paper, a novel region-based active contour model is proposed. Unlike the Chan-Vese model, the energy function of our model only uses information outside the evolving curve. A restriction matrix is introduced for restricting the curve to evolve in the desired region. By minimizing the proposed energy function, the corresponding level set function is obtained. The proposed method has four advantages over the traditional region-based level set methods. First, the level set function is no longer required to be initialized as a sign distance function. Second, due to the simplified level set formulation and its fast curve evolution speed, the level set function does not need to be re-initialized and the computational cost is low. Third, our model is applicable to multiobject images since it can segment objects by separating background from an image. Finally, the proposed model has the property of selective local or global segmentation; it can segment not only the desired object but also the other objects in an image. The advantages of our model are demonstrated using synthetic and real images. C 2011 Society of Photo-Optical