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Automatic building detection from aerial images for mobile robot mapping

机译:从空中图像自动检测建筑物,以进行移动机器人制图

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摘要

To improve mobile robot outdoor mapping, information about the shape and location of buildings is ofudinterest. This paper describes a system for automatic detection of buildings in aerial images taken from a nadir view. The system builds two types of independent hypotheses based on the image contents. A segmentation process implemented as an ensemble of SOMs (Self Organizing Maps) is trained and used to create a segmented image showing different types of roofs, vegetation and sea. A second type of hypotheses is based on an edge image produced from the aerial photo. A line extraction process uses the edge image as input and extracts lines from it. From these edges, corners and rectangles that represent buildings are constructed. A classification process uses the information from both hypotheses to determine whether the rectangles are buildings, unsure buildings or unknown objects.
机译:为了改善移动机器人的室外制图,关于建筑物的形状和位置的信息 udinterest。本文介绍了一种从天底视图拍摄的空中图像中自动检测建筑物的系统。系统基于图像内容建立两种类型的独立假设。训练了作为SOM(自组织图)集合的分割过程,并将其用于创建显示不同类型的屋顶,植被和海洋的分割图像。第二种假设是基于航拍照片产生的边缘图像。线提取过程使用边缘图像作为输入并从中提取线。从这些边缘,构成代表建筑物的角和矩形。分类过程使用来自两个假设的信息来确定矩形是建筑物,不确定建筑物还是未知物体。

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