Abstract

Road traffic sign detection and recognition play an important role in advanced driver assistance systems (ADAS) by providing real-time road sign perception information. In this paper, we propose an improved (Single Shot Detector) SSD algorithm via multi-feature fusion and enhancement, named MF-SSD, for traffic sign recognition. First, low-level features are fused into high-level features to improve the detection performance of small targets in the SSD. We then enhance the features in different channels to detect the target by enhancing effective channel features and suppressing invalid channel features. Our algorithm gets good results in domestic real-time traffic signs. The proposed MF-SSD algorithm is evaluated with the German Traffic Sign Recognition Benchmark (GTSRB) dataset. The experimental results show that the MF-SSD algorithm has advantages in detecting small traffic signs. Compared with existing methods, it achieves higher detection accuracy, better efficiency, and better robustness in complex traffic environment.

Highlights

  • The detection and recognition of road traffic signs are meaningful in advanced driver assistance systems [1] (ADAS) for enhanced driving safety

  • We propose a small traffic sign recognition method that is different from previous ones based on German Traffic Sign Recognition Benchmark (GTSRB) and German Traffic Sign Detection Benchmark (GTSDB) datasets

  • To improve the detection accuracy and speed for small objects, we propose an improved SSD algorithm by jointly exploiting feature fusion and enhanced SSD algorithm MF-SSD

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Summary

Introduction

The detection and recognition of road traffic signs are meaningful in advanced driver assistance systems [1] (ADAS) for enhanced driving safety. INDEX TERMS Traffic sign detection, small target detection, single shot detector, feature fusion, feature enhancement. We propose a small traffic sign recognition method that is different from previous ones based on GTSRB and GTSDB datasets.

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