Improved tensor voting for illusory contour

In this paper we improve the performance of tensor voting over large contour gaps by extending the naive tensor voting techniques. We propose an iterative optimization procedure together with three extensions such as orientation estimation modification, saliency measure revision and edge thinning. As the experimental result shows, the extended tensor voting is more efficient to complete large contour gaps.