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General Road Detection From a Single Image

机译:从单个图像进行一般道路检测

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Given a single image of an arbitrary road, that may not be well-paved, or have clearly delineated edges, or some a priori known color or texture distribution, is it possible for a computer to find this road? This paper addresses this question by decomposing the road detection process into two steps: the estimation of the vanishing point associated with the main (straight) part of the road, followed by the segmentation of the corresponding road area based upon the detected vanishing point. The main technical contributions of the proposed approach are a novel adaptive soft voting scheme based upon a local voting region using high-confidence voters, whose texture orientations are computed using Gabor filters, and a new vanishing-point-constrained edge detection technique for detecting road boundaries. The proposed method has been implemented, and experiments with 1003 general road images demonstrate that it is effective at detecting road regions in challenging conditions.
机译:给定一条任意道路的单个图像,该图像可能未铺好道路,或边缘轮廓清晰,或者某些先验的颜色或纹理分布,计算机是否有可能找到这条道路?本文通过将道路检测过程分解为两个步骤来解决此问题:估计与道路主要(直线)部分相关的消失点,然后根据检测到的消失点对相应的道路区域进行分割。提出的方法的主要技术贡献是一种基于新的自适应软投票方案,该方案基于使用高信心投票者的局部投票区域,并使用Gabor滤波器计算其纹理方向,以及一种用于检测道路的新的消失点约束边缘检测技术边界。所提出的方法已经实施,并且使用1003张普通道路图像进行的实验表明,该方法可有效地检测具有挑战性的道路区域。

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