道路通行障碍物遥感检测与通过性评价

Study of remote sensing detection method for road obstacle and accessibility evaluation

针对现有道路障碍物遥感检测方法对配准精度要求高、受成像条件影响大、自动化程度不高以及需要专业人员操作等不足,提出了一种基于反向特征匹配的道路障碍物检测方法和路段通过性评估方法。该方法基于尺度不变特征变换(scale-invariant feature transform,SIFT)特征提取算法,通过获取灾后影像上道路缓冲区内不能匹配的特征点集来检测定位障碍物,然后采用多种子点区域生长算法获得障碍物分布范围与形状,最后通过与道路矢量数据叠置分析进行路段通过性评价。实验结果表明,该方法能有效地提取因自然灾害而产生的山区公路障碍物位置和面积信息。

In view of the defects of the existing road obstacle detection methods,such as requirement for high registration accuracy,influence by imaging conditions,low-level automation and the need for professional operation,this paper proposes a road obstacle detection method based on reverse feature matching and accessibility evaluation method.On the basis of SIFT feature extraction algorithm,this method detects obstacles by acquiring the set of feature points that are not matched in the road buffer area of the disaster image,then obtains the distribution range and shape of obstacles by using a variety of sub-point region growing algorithms,and finally evaluates the road accessibility by overlapping analysis with road vector data.The experimental results show that this method can effectively extract the position information and shape information of obstacles.