Corner Detection via Topographic Analysis of Vector Potential

Abstract

Abstract This paper describes how corner detection can be realised using a new feature representation based on a magneto-static analogy. The idea is to compute a vector-potential by appealing to an analogy in which the Canny edge-map is regarded as an elementary current density residing on the image plane. In this paper, we demonstrate that corners are located at the saddle-points of the magnitude of the vector-potential. These points correspond to the intersections of saddle-ridge and saddle-valley structures, i.e. to junctions of the edge and symmetry lines. We describe a template-based method for locating the saddle-points. This involves performing a non-minimum suppression test in the direction of the vector-potential and a non-maximum suppression test in the orthogonal direction. Experimental results using both synthetic and real images are given. We investigate the angle and scale sensitivity of the new corner detector and compare it with a number of alternative corner detectors.