Combination of the symmetrical local threshold and the sobel edge detector for lane feature extraction

U. Ozgunalp
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引用次数: 7

Abstract

In this paper, two of lane feature extractors are combined for better lane feature extraction. Namely; the Symmetrical local threshold (SLT) and the Sobel edge detector. The SLT is found to be one of the most robust lane marking feature extractor. However, it relies on the Dark-Light-Dark feature of the painted lane markings. However, in many cases there is no painted lane marking on one or two sides of the road border. Although, edge detector is not assumed to be as good as the SLT for the lane marking feature extraction, it has more advantage on detecting the road borders. Thus, even though many lane marking feature extractors are proposed in the literature, edge detectors are still popular method for lane detection. In this paper, a new approach to combine two of the feature extractors is proposed. With the proposed approach, while detecting painted lane markings accurately, it is possible to detect road borders and poorly painted road markings as well.
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结合对称局部阈值和索贝尔边缘检测器进行车道特征提取
为了更好地提取车道特征,本文将两种车道特征提取器相结合。即;对称局部阈值(SLT)和索贝尔边缘检测器。该方法是一种鲁棒性最好的车道标记特征提取方法。然而,它依赖于深色-浅色-深色的车道标记特征。然而,在许多情况下,在道路边界的一侧或两侧没有涂上车道标记。虽然边缘检测器在车道标记特征提取方面不如SLT,但它在道路边界检测方面更有优势。因此,尽管文献中提出了许多车道标记特征提取器,但边缘检测器仍然是常用的车道检测方法。本文提出了一种结合两种特征提取器的新方法。使用该方法,在准确检测涂漆车道标记的同时,也可以检测道路边界和涂漆不良的道路标记。
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