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A real-time lane detection and tracking algorithm

机译:实时车道检测和跟踪算法

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摘要

Aimed at the problem of lane detection in intelligent vehicle safety aided system, fusing multiple features of the lane, we propose a real-time lane detection and tracking algorithm based on Gabor filter and edge extraction respectively. It can be suitable for fast lane detection on the structured road under the multi-lane and multi-scene. Firstly, in the initial lane detection module, the Gabor filter is used to enhance the characteristics of the lane, and the lane is detected under the restriction of polar angle range by the Hough transform, then using the geometric relationship between the lane and the vehicle to judge the current lane. Secondly, referring the tracking detection module, the lane location of the prior frame is used to establish the dynamic region of interest. The edge of lane is extracted by using the different edge detection operator under the different illumination conditions. Next, the lane is tracked by the least squares fitting in this region. Experimental results indicate that the proposed algorithm is real-time and efficient, and enhance the adaptability for the changing environment of road scene.
机译:针对智能车辆安全辅助系统中的车道检测问题,融合了车道的多个特征,提出了一种分别基于Gabor滤波器和边缘提取的实时车道检测和跟踪算法。它适用于多车道和多场景下的结构化道路上的快速车道检测。首先,在初始车道检测模块中,使用Gabor滤波器增强车道的特性,并通过霍夫变换在极角范围的限制下检测车道,然后利用车道与车辆之间的几何关系判断当前车道。其次,参考跟踪检测模块,将前一帧的车道位置用于建立感兴趣的动态区域。在不同的照明条件下,使用不同的边缘检测算子提取车道边缘。接下来,通过该区域中的最小二乘拟合来跟踪车道。实验结果表明,该算法实时有效,增强了对道路场景变化环境的适应性。

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