A new Bayesian edge-linking algorithm using single-target tracking techniques

This paper proposes novel edge-linking algorithms capable of producing a set of edge segments from a binary edge map generated by a conventional edge-detection algorithm. These proposed algorithms transform the conventional edge-linking problem into a single-target tracking problem, which is a well-known problem in object tracking. The conversion of the problem enables us to apply sophisticated Bayesian inference to connect the edge points. We test our proposed approaches on real images that are corrupted with noise.