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Detection and classification of road signs for automatic inventory systems using computer vision

机译:使用计算机视觉对自动库存系统的路标进行检测和分类

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This article describes an intelligent system that enables the automatic recognition of road signs from image sequences in road environments. The main difficulties the system has to deal with are related to changes in lighting conditions, obstacles blocking the view, the presence of objects with geometric and chromatic similarities and the absence of previous knowledge about their position and orientation. The application of different techniques allows the system to overcome this variety of problems. Therefore, the road sign recognition system is based on a first pre-processing of images, making use of information about road geometry to isolate those areas of the image where road signs may appear. The detection step uses colour and shape analysis to determine the regions of the image where potential road signs may be located. A third step focuses on recognition and classification using pattern matching and edge feature analysis. The proposed algorithm has been tested in different weather and lighting conditions and roads (one and two-lane roads and motorways), overall, a total of 1200 kilometres with a very high success rate of detection and classification as the experimental results show.
机译:本文介绍了一种智能系统,该系统能够从道路环境中的图像序列中自动识别道路标志。该系统必须处理的主要困难与照明条件的变化,阻碍视线的障碍,存在具有几何和色彩相似性的物体以及缺乏有关其位置和方向的先前知识有关。应用不同的技术可以使系统克服各种问题。因此,道路标志识别系统基于图像的第一预处理,利用关于道路几何形状的信息来隔离图像中可能出现道路标志的那些区域。检测步骤使用颜色和形状分析来确定图像中可能存在路标的区域。第三步着眼于使用模式匹配和边缘特征分析的识别和分类。实验结果表明,该算法已经在不同的天气和光照条件下以及道路(一车道和两车道的道路和高速公路)上进行了测试,总长为1200公里,检测和分类的成功率很高。

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