Resource Efficient Hardware Implementation for Real-Time Traffic Sign Recognition

Abstract

Traffic sign recognition (TSR) is one of the Advanced Driver Assistance System (ADAS) device in modern cars. We propose a high efficiency hardware implementation for TSR, which is divided into two stages. In the detection stage, we use Normalized RGB color transform and Single-Pass Connected Component Labeling (CCL) to find the potential traffic signs. In the recognition stage, the Histogram of Oriented Gradient (HOG) is used to generate the descriptor of the signs, and we classify the signs with the Support Vector Machine (SVM). The proposed method achieves 96.61% detection rate and 90.85% recognition rate while testing with the GTSDB dataset. Our hardware implementation reduces the storage of CCL and simplifies the HOG computation. By using TSMC 90nm technology, the proposed design operates at 105 MHz clock rate and processes in 135 fps with the image size of 1360 × 800. The chip size is about lmm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and the power consumption is close to 8mW. Therefore, this work is resource efficient and achieves real-time requirement.