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Lane Markers Detection based on Consecutive Threshold Segmentation

机译:基于连续阈值分割的车道标记检测

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This paper proposed a simple and robust lane markers detection method for intelligent vehicle navigation. It needs not calculate inverse perspective map. The method uses multiple threshold segmentation instead of single threshold segmentation. And straight and curve lane markers are directly extracted in Run-Length accumulation (RLA) images. It performs well in various complex conditions and costs less than 50 ms for a 352 by 288 image. Experiments on many kinds of real complex image sequences demonstrate the effectiveness and efficiency of the proposed method.
机译:提出了一种简单,鲁棒的车道标记检测方法。它不需要计算反透视图。该方法使用多个阈值分割而不是单个阈值分割。直线和曲线车道标记直接从运行长度累积(RLA)图像中提取。对于352 x 288的图像,它在各种复杂条件下的性能都很好,并且成本不到50毫秒。在多种真实复杂图像序列上的实验证明了该方法的有效性和有效性。

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