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Approaches to Design Zigzag Drive Detection Model Using Image Processing

机译:利用图像处理设计曲折驱动检测模型的方法

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It is required to classify the traffic violation for reducing the rate of road accidents and traffic safety. Driver's behavior is one of the main cause that contribute to increase the traffic accidents, as it leads to degrade the performance of driving pattern. This behaviors need to detected and minimize. The paper presented the model, by using video capturing from road side, the diving pattern can be detected. The models then has tested on multiple videos. Mainly two approaches have presented here. Model developed by Canny edge detection method is giving accuracy of 79.16% and model by centroid & blob method is giving accuracy of 83.33%.
机译:为了减少道路交通事故的发生率和交通安全,需要对交通违章进行分类。驾驶员的行为是导致交通事故增加的主要原因之一,因为它会导致驾驶模式的性能下降。这种行为需要检测并最小化。本文提出了该模型,通过从路边拍摄视频,可以检测出潜水模式。然后,模型已在多个视频上进行了测试。这里主要提出了两种方法。 Canny边缘检测方法开发的模型的准确度为79.16%,质心和斑点法开发的模型的准确度为83.33%。

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