结构化道路中车道线的单目视觉检测方法

车道线实时检测是智能车辆视觉导航系统中的重要研究内容.提出了一种基于单目视觉的车道线实时检测方法.首先用Canny边缘检测方法对给定图像进行边缘检测.然后提出一种基于方向优先级的车道线搜索方法,分别对左右车道独立完成搜索,在增强车道线特征的同时削弱其他边缘特征.接下来用霍夫变换计算每条线段的直线度,过滤具有复杂纹理的边缘.最后利用图像的亮度信息及其变换识别出车道线.对提出方法进行了实验验证,结果显示提出方法定位准确,在PIII 933 MHz的CPU上的处理速度平均达每秒13帧,能够满足车辆驾驶的安全性和实时性要求.

Structural road oriented lane detection approach using monocular camera

Lane marking real-time detection is an important research topic of intelligent vehicle vision navigation system. A monocular camera based real-time lane marking detection approach is presented. Firstly, Canny detector is used to obtain the edge map from a given road image. And then, an orientation-priority based searching rules is proposed, which reinforces potential road lines while degrading other edge features. Next, Hough transform is employed to compute the degree of linearity of every edge segment and filter the edges with intricate texture. Finally, the lane markings are identified by the pixel intensity of the image and its transform. Experiment was conducted and results show that the proposed approach can achieve robust and effective localization of lane markings. The approach can run at an average speed of 13 frames per second on a P III 933 MHz CPU, and can meet the requirements of safety and real-time of vehicle driving.