Image segmentation using clique based shape prior and the Mumford Shah Functional

A novel shape prior segmentation model is proposed that utilizes the cliques invariant signature along with a polygonal piecewise constant implementation of the Mumford-Shah Functional. The model will be shown to be useful in the context of difficult segmentation problems including and not limited to segmenting objects amidst clutter, or recognizing objects that contain components with largely varying non-uniform image intensities. In addition, the model will also be shown to be effective for image disocclusion. Lastly, the proposed model can accomplish all the aforementioned tasks both efficiently and with near automation.