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Real-Time Traffic Sign Recognition Using SURF Descriptor

机译:使用SURF描述符的实时交通标志识别

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For road safety, traffic sign is essential for drivers by giving valuable safety and navigation information, pedestrians and even for the development of autonomous driver assistance system. Traffic sign can be classified by two methods can be approached. First approach is color base segmentation which is the region of traffic sign by using HSV color space (Hue, Saturation and Value) and the next approach is shape base segmentation using Hough Circle Detection. In thissystem, we use circle shape base detection for every traffic sign. At first, keypoints descriptor is extracted from each standard traffic sign image in database and then keypoints descriptor is taken from region of traffic sign extracted from Hough circle detection. After that, the nearest distance is matched keypoints descriptor between in each standard traffic sign image in database and extracted traffic sign image.
机译:对于道路安全而言,交通标志通过提供有价值的安全和导航信息对行人,行人乃至自动驾驶辅助系统的开发至关重要。交通标志可以通过两种方法进行分类。第一种方法是使用HSV颜色空间(色相,饱和度和值)进行交通标志区域的颜色基础分割,第二种方法是使用霍夫圆检测技术进行形状基础分割。在此系统中,我们对每个交通标志使用圆形基准检测。首先,从数据库中的每个标准交通标志图像中提取关键点描述符,然后从从霍夫圆检测中提取的交通标志区域中提取关键点描述符。之后,最接近的距离是数据库中每个标准交通标志图像与提取的交通标志图像之间匹配的关键点描述符。

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