<title>Detection of buildings by fusion of range and image data</title>

Abstract

This paper addresses the issue of detecting buildings in aerial images by fusing range data and iconic image information. The range and image data are assumed to be captured by an integrated sensor system from a surveying aircraft. Fusion takes place on a symbolic level of image description. The segmented range data mainly are used for the detection of buildings whereas the image primitives extracted by a grouping algorithm are used for the verification and localization of building hypotheses. Terrain heights can be acquired by an airborne laser scanner. The height data are used to detect local maxima in height which give evidence for objects rising from the terrain surface like buildings do. Because the height data is relatively sparse it is impossible to detect the border lines of the buildings from these data. Therefore candidate regions are examined further by a grouping process. Buildings very often show parallelogram structures in aerial images. The grouping process detects these structures by combining image primitives applying relations like colinearity, parallelism, symmetry, and neighborhood.