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Semantic Traffic Light Understanding for Visually Impaired Pedestrian

机译:视障行人的语义交通灯理解

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A visually impaired pedestrian normally requires information of walking/stop signs with time to decide whether it is available to cross a road on crosswalk. Since traffic lights are installed in verity formats such as, man figure, color and numerical characters, it is complicate to simply understand the meaning. This paper proposes a method of semantic traffic light understand for a visually impaired pedestrian. In the method, a picture of traffic light is initially assumed to extract and type of traffic light are first classified into man figure, color and numerical characters by some classification tools such as signature. In man figure case, color and man gesture are classified and both information are decided base on Fuzzy logic. In the case of numerical characters, they are first enhanced and then classified by a classifier. The experiments have been performed with 200 samples of pedestrian traffic lights and results reveal acceptable accuracy.
机译:视力障碍的行人通常需要时间的步行/停车标志信息,以决定是否可以在人行横道上过马路。由于交通信号灯以诸如人物,颜色和数字字符之类的真实格式安装,因此简单地理解其含义就变得很复杂。本文提出了一种针对视觉障碍行人的语义交通灯理解方法。在该方法中,最初假定提取交通信号灯的图片,然后首先通过一些分类工具(例如签名)将交通信号灯的类型分为人物,颜色和数字字符。在人物模型的情况下,将颜色和手势分类,并基于模糊逻辑确定这两个信息。对于数字字符,首先对其进行增强,然后由分类器对其进行分类。实验已对200个行人交通信号灯样本进行了测试,结果显示出可接受的准确性。

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