摘要
交通标志检测在车辆辅助驾驶系统、自动驾驶等领域是一个重要研究内容,它能即时协助驾驶员或自动驾驶系统有效地检测和识别交通标志。基于该需求,提出了一种基于真实交通场景的交通标志检测方法。首先,选择合适的数据库,将数据库中的道路场景图像转换为灰度图像,并对灰度图像进行简化Gabor滤波处理,强化交通标志的边缘信息。其次,利用区域推荐算法MSERs对Gabor滤波后的特征图进行处理,形成交通标志的推荐区域。最后,通过提取HOG特征,使用SVM进行分类。通过实验,分析了简化Gabor滤波器的特征提取性能、SG-MSERs区域推荐及筛选的性能,并且得到了算法的大类分类准确率以及所需要的处理时间。实验结果表明,所提算法在GTSDB和CSTD数据集上都获得了较好的检测性能,基本满足实时处理的需求。
Traffic sign detection is an important research content in the field of vehicle assistant driving system and automatic driving.It can instantly assist drivers or automatic driving systems to detect and identify traffic signs effectively.Based on this requirement,a traffic sign detection method based on real traffic scene is proposed.Firstly,the appropriate database is selected to convert the road scene image in the database into gray-scale image,and the gray-scale image is processed by simplified Gabor filtering to enhance the edge information of traffic signs.Secondly,the region recommendation algorithm MSERs is used to process the Gabor filtered feature map to form the proposal region of traffic signs.Finally,by extracting hog features,SVM is used for classification.Through experiments,the feature extraction performance of simplified Gabor filter,the performance of SG-MSERs region recommendation and filtering are analyzed,and the classification accuracy and processing time of the algorithm are obtained.The results show that the algorithm achieves good detection performance on both GTSDB and CSTD datasets,and basically meets the needs of real-time processing.
作者
胡聪
何晓晖
邵发明
张艳武
卢冠林
王金康
HU Cong;HE Xiao-hui;SHAO Fa-ming;ZHANG Yan-wu;LU Guan-lin;WANG Jin-kang(College of Field Engineering,Army Engineering University,Nanjing 210007,China)
出处
《计算机科学》
CSCD
北大核心
2022年第S01期325-330,共6页
Computer Science
基金
国家自然科学基金(61671470)。
作者简介
胡聪,born in 1996,postgraduate.His main research interests include computer vision and object detection.1628403930@qq.com;通讯作者:何晓晖,born in 1975,professor.His main research interests include mechatronics and deep learning.gcb202101@163.com。
