摘要
随着社会经济发展,机动车数量增加,智能交通系统将成为时代发展的必然要求。而交通标志识别是智能交通系统的重要环节,更是车辆自动导航的前提,具有重要的研究意义和应用价值。针对4类交通标志,即禁止掉头、禁止前行、禁止左转、禁止右转,从以下几个方面进行研究:(1)基于RGB颜色空间进行阙值分割;(2)通过标志连通域比例进行提取;(3)基于现实情况,构造多场景下的训练集,进行训练识别。实验结果显示,该算法可有效的识别出不同光照条件下发生变形、缩放及旋转后的交通标志牌,交通标志牌识别准确率达到了92%。
With the development of society and economy, the increase in the number of motor vehicles, the intelligent transportation system will become an inevitable requirement for the development of the times. Traffic sign recognition is an important part of ITS,and it is also a precondition in vehicle automatic navigation. So it has important research significance and application value. This article aims at four types of traffic signs,namely,prohibiting U-turn, prohibiting forward turn,no left turn,no right turn,and the following aspects are studied:(1) Threshold segmentation based on RGB color space(2)Extraction based on the proportion of connectivity domain(3)Based on the actual situation, the training set under multi-scene is constructed and trained.The experimental results show that the algorithm can effectively identify the traffic signs with deformation, scaling and rotation under different light conditions,and t the traffic sign recognition accuracy reaches 92%.
出处
《电脑知识与技术》
2018年第4Z期192-195,共4页
Computer Knowledge and Technology
基金
国家自然科学基金面上项目(61471306)
关键词
交通标识
标识提取
标识分割
SVM
traffic identification
dentification extraction
identification segmentation
SVM
