基于多帧视频图像的交通标志实时检测
Real-Time Traffic Sign Detection Based on Multi-Frame Video Images
DOI: 10.12677/CSA.2017.75057, PDF, HTML, XML, 下载: 1,616  浏览: 2,266 
作者: 杨 斐*, 秦 勃：中国海洋大学计算机科学与技术系，山东 青岛；李 伟：枣庄科技职业学院，山东 枣庄
关键词: 交通标志检测；智能交通；空间时序关系模型；Traffic Sign Detection； ITS； Spatial Temporal Model (STM)
摘要: 城市道路交通标志检测是现代智能交通的重要组成部分。本文通过改进基于颜色的图像快速分割算法，对交通标志检测信息进行分割压缩处理，以确保交通标志信息分割的完整性和时效性；并依据交通标志在多帧图像序列中的连续变化关系构建空间时序关系模型(Temporal Spatial Model, STM)，实现交通标志检测候选区域的筛选处理，以降低交通标志检测误检率、提高准确率。实验结果表明，本文提出的算法有效改进了基于单帧图像的交通标志检测方法存在的误检率高问题，满足复杂的城市道路环境下交通标志检测准确率、实效性和鲁棒性的要求。
Abstract: Detection of Urban road traffic sign is an important part of the Modern Intelligent Transportation System (ITS). In order to extract the integral areas of traffic signs and reduce the computation load, this paper has improved the fast color-segment compression algorithm. And, it verifies the traffic sign candidate areas to decrease false positives and raise the accuracy by analyzing the variation in preceding video-images sequence while implementing the proposed Spatial Temporal Model (STM). Experimental results indicate that the accuracy, efficiency and the robustness of the framework are better than the method based on one frame, and it can be applied to detect urban road traffic signs in real time.
文章引用：杨斐, 秦勃, 李伟. 基于多帧视频图像的交通标志实时检测[J]. 计算机科学与应用, 2017, 7(5): 463-472. https://doi.org/10.12677/CSA.2017.75057

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[26] Ruta, A., Li, Y. and Liu, X. (2008) Detection, Tracking and Recognition of Traffic Signs from Video Input. International IEEE Conference on Intelligent Transportation Systems, Beijing, 12-15 October 2008, 55-60.
[27] Soheilian, B., Paparoditis, N. and Vallet, B. (2013) Detection and 3D Reconstruction of Traffic Signs from Multiple View Color Images. ISPRS Journal of Photogrammetry & Remote Sensing, 77, 1-20.
[28] 瓮升霞, 陈一平. 基于移动激光点云的交通标志牌特征提取[J]. 厦门大学学报(自然科学版), 2016, 55(4): 580- 585.
[29] 成健, 张重阳. 基于安卓平台的限速交通标志的检测和识别[J]. 微型电脑应用, 2016, 32(4): 1-4.
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