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ORIENTATION BASED BUILDING OUTLINE EXTRACTION IN AERIAL IMAGES

机译:基于方向的大厦大纲提取在空中图像中

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The goal of this paper is to extract automatically the building contours regardless of shape. By extracting these contours, detection results will be more accurate, giving useful information about urban area, which is important for many tasks, like map updating and disaster management. First, we extract local feature points from the image, based on a modification of Harris detector's saliency function, which can represent urban area and building effectively. This point set is then used to define the main orientation of the buildings, which characterizes well an urban region and helps to define directions, where object contours have to be searched. Second, we applied shearlet approach to extract edges in the defined directions. This results in an edge map, which helps us to determine point subsets belonging to the same building. Convex hulls of the point subsets is used for contour initialization, then region based Chan-Vese Active Contour method is applied to extract the accurate building outlines.
机译:本文的目标是自动提取建筑轮廓,无论形状如何。通过提取这些轮廓,检测结果将更准确,提供有关城市地区的有用信息,这对于许多任务非常重要,例如地图更新和灾难管理。首先,我们根据哈里斯探测器的显着函数的修改,从图像中提取来自图像的本地特征点,这可以有效地代表城市地区和建筑物。然后,使用该点集来定义建筑物的主要方向,该建筑物的主导是一种城市区域,并有助于定义要搜索的对象轮廓的方向。其次,我们施加了剪切方法来提取定义方向的边缘。这导致边缘图,这有助于我们确定属于同一建筑物的点子集。点子集的凸壳用于轮廓初始化,然后应用了基于区域的Chan-Vese Active Contour方法来提取准确的建筑轮廓。

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