首页> 外文会议>IASTED International Conference on Signal and Image Processing and Applications >AN ADAPTIVE APPROACH TO DETECT WARNING TRAFFIC SIGNS USING SOM AND WINDOWED HOUGH TRANSFORM
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AN ADAPTIVE APPROACH TO DETECT WARNING TRAFFIC SIGNS USING SOM AND WINDOWED HOUGH TRANSFORM

机译:使用SOM和Windowed Hough变换检测警告交通标志的自适应方法

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Warning traffic signs represent an important group of traffic signs which indicate danger for road users. Detecting this group in good time may be helpful to avoid many fatal accidents. This paper presents a new approach to detecting warning traffic signs which is based on color segmentation using Self Organizing Maps and windowed Hough Transform. The proposed system is a standalone and adaptive which means that it works without any kind of training. This is due to the fact that color segmentation using SOM employs 1% of the image under investigation for the training and Hough Transform is invoked to detect the shape of this group of traffic signs. Experiments conducted to check the robustness of this approach indicated that 95.6% of the traffic signs invoked for this test were successfully detected. This test was carried out under a wide range of environmental conditions and in different European countries.
机译:警告交通标志代表了一组重要的交通标志,表明道路使用者的危险。在好时机中检测这个群体可能有助于避免许多致命事故。本文介绍了一种新方法来检测基于使用自组织地图和窗口的Hough变换基于颜色分割的警告交通标志的方法。建议的系统是一个独立的和自适应,这意味着它没有任何培训。这是由于使用SOM的颜色分割使用1%的图像,在调查训练和霍夫变换中被调用以检测该组交通标志的形状。进行检查的实验检查该方法的稳健性表明,95.6%的95.6%已成功检测用于该测试的交通标志。该测试是在广泛的环境条件下和不同欧洲国家进行的。

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