Corner Detection Using Morphological Skeleton: An Efficient and Nonparametric Approach

Abstract

In this paper we propose an effective and robust approach for detecting corner points on a given binary image. Unlike other corner detection methods the proposed method is non-parametric in nature, that is, it does not require any input parameter. The proposed method is based on mathematical morphology. It makes use of morphological skeleton for detecting corner points. Convex corner points are obtained by intersecting the morphological boundary and the corresponding skeleton, where as the concave corner points are obtained by intersecting the boundary and the skeleton of the complement image. Experimental results show that the proposed method is more robust and efficient in detecting corner points.