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A Machine Vision System for Lane-Departure Detection

机译:用于车道偏离检测的机器视觉系统

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This paper presents a feature-based machine vision system for estimating lane-departure of a traveling vehicle on a road. The system uses edge information to define an edge distribution function (EDF), the histogram of edge magnitudes with respect to edge orientation angle. The EDF enables the edge-related information and the lane-related information to be connected. Examining the EDF by the shape parameters of the local maxima and the symmetry axis results in identifying whether a change in the traveling direction of a vehicle has occurred. The EDF minimizes the effect of noise and the use of heuristics, and eliminates the task of localizing lane marks. The proposed system enhances the adaptability to cope with the random and dynamic environment of a road scene and leads to a reliable lane-departure warning System.
机译:本文提出了一种基于特征的机器视觉系统,用于估计道路上行驶车辆的车道偏离。该系统使用边缘信息来定义边缘分布函数(EDF),即边缘幅度相对于边缘方向角的直方图。通过EDF,可以连接边缘相关信息和车道相关信息。通过局部最大值和对称轴的形状参数检查EDF,可以识别是否发生了车辆行驶方向的变化。 EDF将噪声的影响和启发式方法的使用降至最低,并消除了定位车道标记的任务。所提出的系统增强了适应道路场景的随机和动态环境的适应性,并导致了可靠的车道偏离警告系统。

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