一种圆形禁令交通标志快速提取和识别方法
A Quickly Detecting and Recognition Method for Circular Ban Traffic Signs
摘要: 随着社会的发展,智能交通系统的开发受到广泛的关注,交通标志识别系统作为智能交通的一部分,如何对其快速的提取并识别开始被越来越多的人关注和研究。本文提出一种基于RGB空间的圆形禁令交通标志的提取与识别算法,该方法根据标志的颜色特征和形状特征,通过RGB空间阈值分割和最小二乘椭圆拟合过滤的方法对交通标志进行检测,最后利用BP人工神经网络构建最佳识别网络,达到自动识别圆形禁令交通标志的目的。实验结果表明,该方法具有较好的提取和识别能力。
Abstract: With the development of the society, the intelligent transportation system has been widely focused on. More and more people are paying attention to traffic sign recognition system, which as a part of the entire intelligent transportation system. This paper put forward a method, which based on RGB space, to detect and to recognize circular ban traffic signs. This method uses threshold segmentation in RGB space and the least-squares ellipse fitting to filter and detect traffic signs, due to their color features and shape features. At last, the method uses BP artificial neural network to build the best recognition network to automatically recognize circular ban traffic signs. The experimental results show that the method has good detect and recognize ability.
文章引用:陈力, 李迎松. 一种圆形禁令交通标志快速提取和识别方法[J]. 测绘科学技术, 2016, 4(2): 45-52. http://dx.doi.org/10.12677/GST.2016.42006

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http://dx.doi.org/10.1109/iecon.1996.570749
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[30] 陈维馨. 道路交通标志检测技术研究[D]: [硕士学位论文]. 厦门: 厦门大学, 2007.
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http://dx.doi.org/10.1109/ICMLC.2002.1176714
[32] Maldonado-Bascon, S., Lafuente-Arroyo, S., Gil-Jimenez, P., Gomez-Moreno, H. and Lopez-Ferreras, F. (2007) Road-Sign Detection and Recognition Based on Support Vector Machines. IEEE Transactions on Intelligent Transportation Systems, 8, 264-278.
http://dx.doi.org/10.1109/TITS.2007.895311
[33] 黄志勇, 孙光民, 李芳. 基于RGB视觉模型的交通标志分割[J]. 微电子与计算机技术, 2004, 21(10): 147-152.
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http://dx.doi.org/10.1002/(SICI)1097-0258(20000229)19:4<541::AID-SIM355>3.0.CO;2-V