Real-Time Traffic Sign Detection via Color Probability Model and Integral Channel Features

摘要：

　　This paper aims to deal with real-time traffic sign detection.To this end,a two-stage method is proposed to reduce the processing time with little influence to AUC (area under curve) value.In first stage,a color probability model is proposed to transform an input image to probability maps.The traffic sign proposals are then extracted by finding maximally stable extremal regions on these maps.In second stage,an integral channel features detector is employed to remove false positives of the proposals.Experiments on the GTSDB benchmark 1 show that the proposed color probability model achieves the highest recall rate and the proposed two-stage method significantly improves computational efficiency with good AUC value in comparison with the state-of-the-art methods.

关键词： Color Probability Model MSER Integral Channel Features Traffic Sign Detection Real-Time

作者: Yi Yang Fuchao Wu

作者单位: Institute of Automation,Chinese Academy of Sciences,Beijing,China

会议类型: 国际会议

会议名称: Chinese Conference on Pattern Recognition, CCPR(2014年全国模式识别学术会议)

会议地点: 长沙

会议语种:英文

页码: 545-554

在线出版日期: 2014-11-01（万方平台首次上网日期，不代表论文的发表时间）