A Shape Detection Method Based on the Radial Symmetry Nature and Direction-Discriminated Voting

This paper describes a new method for shape detection based on the radial symmetry nature and direction-discriminated voting. Multiple shapes including circles, regular and non-regular polygons can be detected under a general framework. The novelty of our approach is that different shapes can be simultaneously located and classified. It is implemented by taking account of both voting accumulations and voting directions. We show that the approach can reduce false detection and computation burden compared to some existing methods. Moreover, by modeling a shape based on its partial radial symmetry characteristics and the geometrical relationship among the symmetry centers, our approach is extended to detect non-regular polygons. Experiments on traffic sign detection demonstrate good performance of our method.