Automatic building detection from aerial images for mobile robot mapping

Abstract

To improve mobile robot outdoor mapping, information about the shape and location of buildings is of interest. 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 snowing 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.