一种基于帧间关联的实时车道线检测算法

Real-time Lane Detection Algorithm Based on Inter-frame Correlation

为了更好地满足车道线检测的实时性和鲁棒性要求,提出一种基于帧间关联的车道线检测算法。根据道路图像的特征,将图像灰度化后,采用中值滤波去除图像采集过程中引入的噪声,再根据自适应阈值边缘提取检测算法,在提取过程中对原图像进行区域划分,利用改进的Hough变换得到车道候选线,建立动态的ROI,通过帧间关联方法实现对车道线模型的约束和更新。实验结果表明,基于帧间关联的车道线检测方法不仅降低了图像数据的运算量,缩减了算法的执行时间,而且提高了算法的鲁棒性。

In order to meet the requirements of the real-time and robustness of lae detection algorithm,a real-time lane detection algorithm based on inter-frame correlation was proposed.According to the characteristics of the road image,noise is filtered out by median filter and the lane mark edge is extracted by adaptive threshold for lane detection firsly.Then,the original image is divided beyond the extraction process.It gets lane candidate lines by improving Hough transform and builds dynamic ROI.Finally,the lane line model by inter-frame correlation is updated and restricted.The results show that the operation amount of image data is simplified,the runtime of the algorithm is reduced,and the robustness of the algorithm is greatly improved.