Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W1, 227-232, 2013
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-1-W1/227/2013/
doi:10.5194/isprsarchives-XL-1-W1-227-2013
© Author(s) 2013. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
02 May 2013
MULTIDIRECTIONAL BUILDING DETECTION IN AERIAL IMAGES WITHOUT SHAPE TEMPLATES
A. Manno-Kovacs and T. Sziranyi Pazmany Peter Catholic University, Prater 50/A, 1083, Budapest, Hungary
MTA SZTAKI, Kende 13-17, 1111, Budapest, Hungary
Keywords: Directional Classification, Building Detection, Feature Extraction, Aerial Image Detection Abstract. The aim of this paper is to exploit orientation information of an urban area for extracting building contours without shape templates. Unlike using shape templates, these given contours describe more variability and reveal the fine details of the building outlines, resulting in a more accurate detection process, which is beneficial for many tasks, like map updating and city planning. According to our assumption, orientation of the closely located buildings is coherent, it is related to the road network, therefore adaptation of this information can lead to more efficient building detection results.

The introduced method first extracts feature points for representing the urban area. Orientation information in the feature point neighborhoods is analyzed to define main orientations. Based on orientation information, the urban area is classified into different directional clusters. The edges of the classified building groups are then emphasized with shearlet based edge detection method, which is able to detect edges only in the main directions, resulting in an efficient connectivity map. In the last step, with the fusion of the feature points and connectivity map, building contours are detected with a non-parametric active contour method.

Conference paper (PDF, 2042 KB)


Citation: Manno-Kovacs, A. and Sziranyi, T.: MULTIDIRECTIONAL BUILDING DETECTION IN AERIAL IMAGES WITHOUT SHAPE TEMPLATES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W1, 227-232, doi:10.5194/isprsarchives-XL-1-W1-227-2013, 2013.

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