A randomized circle detection method with application to detection of circular traffic signs

Abstract

We propose an improved randomized circle detection method. The improved method reduces the computational complexity of the randomized circle detection method by a factor of two. We then apply the proposed method to detection of circular traffic signs. For traffic images taken in complex scenarios, the colors of interest are first segmented, obtaining potential regions of traffic signs. By applying edge detection and improved randomized circle detection method, traffic signs can be exactly located. Experimental results show that the proposed method has a small computational requirement for natural scenes under different lighting conditions and it can fast and accurately locate circular traffic signs. It can also position circular traffic signs with occlusions and variations in shape, size, and color.