Detection for Deformed and Sheltered Circular Traffic Signs

College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China

Abstract

In this paper, a simple and efficient algorithm for detecting deformed and sheltered circular traffic signs under the complex natural scenes is proposed. First, the image is segmented by adaptive hybrid gradation method. Then the circular traffic sign will be detected by an enhanced random eclipse fitting method. The experimental results show the detection rate reaches 96.37%, and the proposed algorithm can succeed to detect most of circular traffic signs in complex conditions and handle the adverse influence of traffic signs’ deformation, occlusion and the background interference whose colors are as same as traffic signs’ well in particular.