结合Hough变换与运动估计的车道线提取方法

Combining Hough Transform and Motion Estimation Method for Lane Recovering

车道线识别是安全辅助驾驶和智能驾驶系统的核心研究内容,对控制危险驾驶和疲劳驾驶均有显著的作用,通常利用Hough变换对直线检测的容错性和鲁棒性,可以对车载摄像头拍摄到的车道线进行有效的检出。巧妙地将分块Hough变换和图像块的运动估计相结合,极大地降低了车道线检测和跟踪的算法复杂度,实现了车道线的实时识别与跟踪。实验表明,采用该方法既可以得到稳定的检测结果,又能提高检测的速度,保留了Hough变换的容错性和鲁棒性。

The lane recognition is the core contents of the safe driver assistance and intelligent driving system, control of dangerous driving and driver fatigue have a significant role. Usually the Hough transform for line detection of fault-tolerance and robustness, can be taken on-board camera for effective detection of the lane. This paper cleverly combines the blocked Hough transform and motion estimation of the block, greatly reduces the lane detection and tracking algorithm complexity, realizes the lane line real-time recognition and tracking. The experiments show that this method can not only be stable test results,but also improve the detection speed, and retain the Hough transform fault tolerance and robustness.