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Real-time recognition of road traffic signs in video scenes

机译:视频场景中道路交通标志的实时识别

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摘要

This paper presents a new algorithm for the detection and classification of real-time road traffic signs in the video. Our system is able to detect and classify triangular, circular, and octagonal signs of red and blue colors. The proposed system operates into two processing steps: (1) detection and (2) classification road signs. The system has detected candidate regions as Maximally Stable Extremal Regions (MSERs) in HSV color space with available robustness to variations in lighting conditions, especially red and blue. The detected candidate regions were then classified as method template matching, such as circular, octagonal, and triangular shapes. The proposed system is operating under a range of weather conditions and recognizes all classes of road traffic sign database. Results show a high success rate. In fact, the system maintains high performance for detection and classification steps whose F-measure are set to 0.95 and 0.92 respectively. We conclude, from these results, that the proposed system is invariant to rotation, translation, scale, even to partial occlusions. Moreover, results prove that the system is suitable and reliable for real-time processing.
机译:本文提出了一种用于视频中实时道路交通标志的检测和分类的新算法。我们的系统能够检测和分类红色和蓝色的三角形,圆形和八边形符号。拟议的系统分为两个处理步骤:(1)检测和(2)分类路标。该系统已检测到候选区域为HSV颜色空间中的最大稳定极端区域(MSER),并具有针对照明条件(尤其是红色和蓝色)变化的可用鲁棒性。然后将检测到的候选区域分类为方法模板匹配,例如圆形,八边形和三角形。拟议的系统在一定范围的天气条件下运行,并且可以识别所有类别的道路交通标志数据库。结果显示出很高的成功率。实际上,该系统在F-measure分别设置为0.95和0.92的检测和分类步骤中保持较高的性能。从这些结果我们可以得出结论,所提出的系统对于旋转,平移,缩放甚至部分遮挡都是不变的。此外,结果证明该系统适合实时处理。

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