厦门大学学报（自然科学版）2011，Vol.50Issue(4)：685-689,5.
基于颜色分割和多特征融合的交通标志检测
Traffic Sign Detection Based on Color Segmentation and Multi-features Fusion
摘要
Abstract
Traffic sign detection is important in intelligent transport system. In this paper,an efficient novel approach is proposed to achieve automatic traffic sign detection. The detection method combines color segmentation with learning based multi-features of traffic sign guided search. The rough location stage could obtain possible region of traffic sign using color segmentation based on YIQ space. The exact location stage searches traffic sign in these traffic sign possible regions based on multi-features fusion, we use histogram of oriented gradient (HOG) and local binary pattern (LBP) to classify by support vector machine (SVM). Experimental results show that,the proposed approach can achieve robustness to illumination,scale,viewpoint change and even partial occlusion. The average detection rate and the false positive rate of our approach are better than the method based on one feature.关键词
交通标志检测/颜色分割/梯度方向直方图/局域二值模式Key words
traffic sign detection/color segmentation/HOG/ LBP分类
信息技术与安全科学引用本文复制引用
卢盛荣,刘礼锋,李翠华..基于颜色分割和多特征融合的交通标志检测[J].厦门大学学报（自然科学版）,2011,50(4):685-689,5.基金项目
国防基础科研计划项目(B1420110155) （B1420110155）
国家重点基础研究发展计划(973)项目(2007CB311005) （973）
福建省教育厅A类项目(JA09230,JA09231) （JA09230,JA09231）
