A real-time histographic approach to road sign recognition

This paper presents the development and real-time implementation of an algorithm capable of recognizing stop, yield, and do-not-enter traffic warning signs. It consists of six modules: color segmentation, edge localization, RGB differencing, edge detection, histograph extraction, and classification. RGB transformed pixels are sparsely segmented and sequentially XOR-ed to localize edge areas. RGB differencing together with maxima edge detection is then deployed to locate edges in these areas. Recognition is achieved based on the angular histographic attribute extracted by a semi-rectangular histographic mask. All the modules are implemented on the TMS320C40 DSP processor allowing video data captured by a video camera to be processed in real-time. The devised real-time processing platform has led to an understanding of various environmental effects on video data