文献类型：期刊文献

中文题名：基于YOLO v3的交通标志牌检测识别

英文题名：Traffic sign detection and recognition based on YOLO v3

作者：潘卫国[1,2];刘博[3];陈英昊[3];石洪丽[3]

第一作者：潘卫国

机构：[1]北京联合大学北京市信息服务工程重点实验室,北京100101;[2]北京联合大学机器人学院,北京100027;[3]北京联合大学应用科技学院,北京100101

第一机构：北京联合大学北京市信息服务工程重点实验室

年份：2019

卷号：38

期号：11

起止页码：147-150

中文期刊名：传感器与微系统

外文期刊名：Transducer and Microsystem Technologies

收录：CSTPCD;;CSCD:【CSCD_E2019_2020】；

基金：国家自然科学基金资助项目(61802019,61871039);北京市教育委员会科技计划资助项目(KM201711417005,KM201911417001)

语种：中文

中文关键词：目标检测;感兴趣区域;深度学习;交通标志牌

外文关键词：object detection;region of interest(ROI);Deep learning;traffic sign

摘要：在无人驾驶和辅助驾驶领域,交通标志牌检测识别是重要的。针对目前基于YOLO的检测方法能够达到实时的检测效果,但在准确率方面有所降低的问题,提出了基于感兴趣区域(ROI)的交通标志牌检测方法。首先根据交通标志牌的颜色特性得到候选区域;再利用交通场景图像规则确定交通标志牌的ROI;最后在交通标志牌的ROI,基于YOLO v3实现对交通标志牌的检测识别。实验结果表明:由于本文提出的方法去除了图像中部分干扰因素,使得算法在检测精度上得到了提升,也能满足实时性的需求,并在无人驾驶车辆上进行了验证。
In the field of self-driving and driver assistance system,traffic sign detection and recognition is very important.Aiming at that current detection method based on YOLO can achieve real-time detection effect,but the accuracy is decreased,problem,a traffic sign detection method based on region of interest(ROI)is presented. color features of traffic sign are firstly used to get the candidate regions.Secondly,ascertain the ROI of traffic sign based on the rules of traffic scene image.Finally detect traffic sign in ROI based on YOLO v3.The experimental result show that self-driving or intelligent vehicle show that the proposed approach eliminate partial interference which makes the detection precision of algorithm is improved and can meet the needs of real-time performance.It is verified in remotely pilotod vehile.