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Two algorithms for detection of mutually occluding traffic signs

机译:两种互斥交通标志的检测算法

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The robust identification of the traffic signs represents the first and one of the most important steps in the development of a traffic sign recognition (TSR) system. Traffic signs detection usually involves a color segmentation process that uses the information related to the chromatic properties of the road signs. Since the traffic video data is captured in diverse road and weather conditions, the problem relating to traffic sign detection is quite challenging. Among several issues that need to be addressed during this processing stage, the problem generated by mutually occluding traffic signs (mutual occlusion occurs when one traffic sign partially occludes the surface of other road signs) that are attached to the same pole require special attention. In these situations the color segmentation process fails to correctly identify the regions that are associated with the traffic signs. These traffic sign detection failures compromise the performance of other stages of the TSR system and in this paper we propose two approaches that address the segmentation of mutually occluding traffic signs. The first approach uses the information associated with the inner parts of the traffic signs, while the second approach applies the watershed transform to identify the signs that have their borders in contact or are mutually occluding.
机译:交通标志的可靠识别是交通标志识别(TSR)系统开发的第一步和最重要的步骤。交通标志检测通常涉及颜色分割过程,该过程使用与道路标志的色度特性有关的信息。由于交通视频数据是在不同的道路和天气条件下捕获的,因此与交通标志检测有关的问题非常具有挑战性。在此处理阶段需要解决的几个问题中,由相互闭塞的交通标志(相互交叉闭塞(当一个交通标志部分遮挡其他道路标志的表面时会发生相互闭塞))产生的问题需要特别注意。在这些情况下,颜色分割过程无法正确识别与交通标志关联的区域。这些交通标志检测失败影响了TSR系统其他阶段的性能,在本文中,我们提出了两种方法来解决相互阻塞交通标志的分割问题。第一种方法使用与交通标志内部相关的信息,而第二种方法应用分水岭变换来识别边界接触或相互遮挡的标志。

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