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Localization and recognition of traffic signs for automated vehicle control systems

机译:自动车辆控制系统的交通标志的本地化和识别

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Abstract: We present a computer vision system for detection and recognition of traffic signs. Such systems are required to assist drivers and for guidance and control of autonomous vehicles on roads and city streets. For experiments we use sequences of digitized photographs and off-line analysis. The system contains four stages. First, region segmentation based on color pixel classification called SRSM. SRSM limits the search to regions of interest in the scene. Second, we use edge tracing to find parts of outer edges of signs which are circular or straight, corresponding to the geometrical shapes of traffic signs. The third step is geometrical analysis of the outer edge and preliminary recognition of each candidate region, which may be a potential traffic sign. The final step in recognition uses color combinations within each region and model matching. This system maybe used for recognition of other types of objects, provided that the geometrical shape and color content remain reasonably constant. The method is reliable, easy to implement, and fast, This differs form the road signs recognition method in the PROMETEUS. The overall structure of the approach is sketched. !8
机译:摘要:我们提出了一种用于检测和识别交通标志的计算机视觉系统。需要这样的系统来辅助驾驶员以及在道路和城市街道上引导和控制自动驾驶车辆。对于实验,我们使用数字化照片序列和离线分析。该系统包含四个阶段。首先,基于称为SRSM的彩色像素分类进行区域分割。 SRSM将搜索限制在场景中感兴趣的区域。其次,我们使用边缘跟踪来找到标志的外边缘部分,这些部分是圆形或笔直的,与交通标志的几何形状相对应。第三步是对外边缘进行几何分析并初步识别每个候选区域,这可能是潜在的交通标志。识别的最后一步使用每个区域内的颜色组合和模型匹配。如果几何形状和颜色含量保持合理恒定,则该系统可用于识别其他类型的对象。该方法可靠,易于实施和快速,这与PROMETEUS中的路标识别方法不同。概述了该方法的总体结构。 !8

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