Polyhedral object recognition using Hough-space features

Abstract We propose a new technique for three-dimensional (3-D) polyhedral object recognition on the basis of a single two-dimensional (2-D) view of a 3-D scene. The binary gradient image of the captured scene is converted into the Hough-space domain. The cluster patterns originating from straight-line features of the image are explored by reasoning in Hough space. This yields an attributed graph representation of the object to be recognized which is compared to similar representations of CAD-designed wire frame model objects by means of a new attributed subgraph isomorphism algorithm. Simulation experiments illustrate this promising new approach.