首页> 外文会议>Recent Advances in Space Technologies, 2005. RAST 2005. Proceedings of 2nd International Conference on >Building damage detection from post-earthquake aerial imagery using building grey-value and gradient orientation analyses
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Building damage detection from post-earthquake aerial imagery using building grey-value and gradient orientation analyses

机译:使用建筑物灰度值和梯度方向分析从地震后航空影像中检测建筑物损坏

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The collapsed buildings due to 1999 Kocaeli earthquake were detected from post-event panchromatic aerial imagery based on grey-value and the gradient orientation of the buildings. The building boundaries were available and stored in a GIS as vector polygons. The building polygons were utilized to perform the assessments in a building specific manner. The approach was implemented in a selected area of Golcuk, which is one of the urban areas most strongly hit by the earthquake. First, the buildings were selected one-by-one from the integrated vector (building boundaries) and raster (aerial photo) data set. The building damage detection process was then divided into two branches. In the first branch, the detection was performed using the building grey-value information. To do that, a greyvalue threshold (T1) was determined for discriminating the collapsed buildings from the un-collapsed ones. In the second branch, a group of operations including the gradient calculation and the determination of gradient orientation were performed. By utilizing the orientation information, an optimum threshold level (T2) was determined for the standard deviation of the angle distribution of the building pixels. When assessing the condition of a building, the results of the two branches were combined and a final decision was made in an integrated manner. Of the 284 buildings analyzed, 254 were labeled correctly as collapsed or un-collapsed providing an overall accuracy of 89.44%. The results reveal that the collapsed buildings due to the earthquake can be successfully detected from post-event aerial images.
机译:根据建筑物的灰度值和梯度方向,从事后的全色航拍图像中检测出1999年Kocaeli地震造成的倒塌建筑物。建筑物边界可用,并作为矢量多边形存储在GIS中。利用建筑物多边形以特定于建筑物的方式执行评估。该方法已在Golcuk的选定地区实施,该地区是遭受地震最严重的城市之一。首先,从综合矢量(建筑物边界)和栅格(航空照片)数据集中一个一个地选择建筑物。然后将建筑物损坏检测过程分为两个分支。在第一分支中,使用建筑物灰度值信息执行检测。为此,确定灰度值阈值(T1),以将倒塌的建筑物与未倒塌的建筑物区分开。在第二分支中,执行包括梯度计算和梯度取向的确定的一组操作。通过利用方向信息,为建筑物像素的角度分布的标准偏差确定了最佳阈值水平(T2)。在评估建筑物的状况时,将两个分支的结果进行合并,并以综合方式做出最终决定。在分析的284座建筑物中,有254座被正确标记为倒塌或未倒塌,总体准确性为89.44%。结果表明,可以从事后航空图像中成功检测到由于地震而倒塌的建筑物。

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