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Localization and recognition of traffic signs for automated vehicle control systems

机译:自动化车辆控制系统的交通标志的本地化和识别

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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.
机译: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。需要这些系统来帮助驾驶员和道路和城市街道上自治车辆的指导和控制。对于实验,我们使用数字化照片和离线分析的序列。系统包含四个阶段。首先,基于颜色像素分类的区域分割称为SRSM。 SRSM将搜索限制在场景中的兴趣区域。其次,我们使用边缘跟踪来找到圆形或直线的迹象的部分,对应于交通标志的几何形状。第三步是每个候选区域的外边缘的几何分析,并且可以是潜在的交通标志。识别的最后一步使用每个区域内的颜色组合和模型匹配。该系统可以用于识别其他类型的物体,只要几何形状和颜色内容保持合理恒定。该方法可靠,易于实施,快速,这不同,使得普罗迪斯的道路标志识别方法形成。速写了该方法的整体结构。

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