Robust traffic sign detection using fuzzy shape recognizer

Abstract

A novel fuzzy approach for the detection of traffic signs in natural environments is presented. More than 3000 road images were collected under different weather conditions by a digital camera, and used for testing this approach. Every RGB image was converted into HSV colour space, and segmented by the hue and saturation thresholds. A symmetrical detector was used to extract the local features of the regions of interest (ROI), and the shape of ROI was determined by a fuzzy shape recognizer which invoked a set of fuzzy rules. The experimental results show that the proposed algorithm is translation, rotation and scaling invariant, and gives reliable shape recognition in complex traffic scenes where clustering and partial occlusion normally occur.