为了在面向交通流监测的航摄图像分析中，使用模板匹配的方法提取道路交通流信息，需要首先计算道路区域的位置和用于追踪道路的模板。实时自动地提取用于识别道路的种子点和追踪模板，为此提出了一种一维无标记分水岭分割方法，需要简单的图像特征计算，不需要人工标记。通过计算道路截面极值，提取波谷区域，然后计算区域相似度，合并相似区域得到分割结果；通过对区域进行排名，并进行区域内放射搜索，识别出道路区域，计算道路追踪模板。结果表明与 Canny边缘提取和 Hough直线提取结果相比，人工干预较少；且数据处理量减小、道路提取效率提高；模板计算结果较好。

In order to extract the road traffic flow information using UAV images, it is necessary to calculate the location of the road area and generate the road template for road tracking. Real-time calculation requires automated seed points extraction for identifying road and generating tracing template. A one-dimensional unmarked watershed segmentation method is proposed, which needs to calculate using the simple image feature, and don't need manual seed points mark. Firstly, by recognizing sectional extremum in the profile of source image road, the valley regions are extracted between extremums and the similarity is calculated through the region. Then, combine the nearly similar regions, get the segmentation results. Secondly, rank the segmentation regions, search radiology in the ranked regions, and identify the road area and calculate road track template. Experimental results show that the method need less manual intervention and more efficiency than the Canny edge extraction and Hough line extraction under the same conditions. By fitting the road edge points by the least squares method to get the direction of the road, the calculation of road direction is accurate, and the calculated tracking template is consistent with the actual that.