计算机工程与应用2019，Vol.55Issue(18)：195-200,6.DOI:10.3778/j.issn.1002-8331.1806-0155
基于多特征融合的交通标志识别算法
Traffic Sign Recognition Algorithm Based on Multiple-Feature Fusion
摘要
Abstract
Taking recognition rate, time complexity and robustness all into consideration, this paper proposes a traffic sign recognition algorithm based on edge, texture and color feature fusion and Support Vector Machine(SVM). It con-ducts the statistical average on extracted Histogram of Oriented Gradien(t HOG)features which can describe the edge information of traffic signs images. The reduced-dimension HOG-maxLBP features are obtained by fusing with Local Bi-nary Pattern(LBP)features that can represent traffic sign internal texture information. The color features are concatenated with HOG-maxLBP features as the final features. Traffic sign training and classification are performed using SVM. Experi-mental results show that the proposed algorithm not only improves the traffic sign recognition rate, but also reduces the time complexity and enhances the system robustness.关键词
交通标志识别(TSR)/方向梯度直方图(HOG)/局部二值模式(LBP)/颜色特征/特征融合/支持向量机(SVM)Key words
Traffic Sign Recognition(TSR)/Histogram of Oriented Gradien(t HOG)/Local Binary Pattern(LBP)/color features/feature fusion/Support Vector Machine(SVM)分类
信息技术与安全科学引用本文复制引用
韩习习,魏民,徐西义,李巧月,陈曦,祝汉城..基于多特征融合的交通标志识别算法[J].计算机工程与应用,2019,55(18):195-200,6.基金项目
国家自然科学基金(No.61771473,No.61379143). （No.61771473,No.61379143）
