西华大学学报（自然科学版）2016，Vol.35Issue(1)：89-93,5.DOI:10.3969/j.issn.1673-159X.2016.01.019
基于颜色特征和SVM的交通标志检测
Traffic Sign Detection Based on Color Feature and SVM
摘要
Abstract
Focused on the problem of time consumption and accuracy of traffic sign recognition system,an efficient algorithm for traf-fic sign detection based on improved color detection in RGB color space combined with support vector machine is presented. Firstly,the histogram equalization and Gabor filter are applied for image enhancement to highlight the image color. Secondly, an improved color de-tection method is proposed to select the coarse candidate areas. Thirdly, a SVM classifier is trained using HOG feature for further detec-tion and shape judgment. Comperative tests are done about detection accuracy and detection time consumption. The experimental results show that this algorithm testing time is short, error detection rate and false detection rate are low. The algorithm can detect signs quickly and determine the shape. It can also deal with various cases such as images with low brightness, rotation and partial occlusion with high accuracy. Compared with color enhancement algorithm, this method can achieve better accuracy and has less time consumption.关键词
交通标志检测/直方图均衡化/Gabor滤波/颜色检测/SVM分类器Key words
traffic sign detection/histogram equalization/Gabor filter/color detection/SVM( support vector machine) classifier分类
信息技术与安全科学引用本文复制引用
李光瑞,夏凌,杜健,强策..基于颜色特征和SVM的交通标志检测[J].西华大学学报（自然科学版）,2016,35(1):89-93,5.基金项目
教育部春晖计划合作科研项目(Z2011090). （Z2011090）
