一种新的车道线快速识别算法

针对现有的的车道线识别算法在复杂环境下识别率低、鲁棒性和实时性较差的问题，提出了一种基于形态学多结构元素建模的车道线快速识别算法。该算法首先对车道图像进行感兴趣区域提取，通过Canny算子对感兴趣区域进行边缘检测，然后利用具有车道模型特征的多结构元素进行车道线提取、霍夫变换，以及峰值检测点参数的筛选，从而得到实际车道左右标识线的参数以重建原车道线。仿真实验表明，该算法能在多种复杂环境下快速、准确地识别出车道标识线，且鲁棒性高。

Novel algorithm of fast lane identification

The existing lane recognition algorithms have low recognition ratio, bad robustness and real-time, for overcoming these drawbacks, this paper proposed a fast algorithm of lane recognition based on multi-structure elements model of morphological. In the algorithm, the interested area is extracted from original image, which is detected by the operator of Canny. After that, the lanes are extracted by the structure elements, which have similar characteristics to that of lane model. Several lines are detected by Hough transformation, and choose the parameters to reconstruct the traffic lane. Experiments show that this algorithm is simple, has better robustness, and at the same time, can efficiently detect the lane mask accurately and quickly.