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Proceedings Paper

L-shaped corner detector for rooftop extraction from satellite/aerial imagery
Author(s): Hui Li Tan; Jiayuan Fan; Shijian Lu
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Paper Abstract

Rooftop extraction from satellite/aerial imagery is an important geospatial problem with many practical applications. However, rooftop extraction remains a challenging problem due to the diverse characteristics and appearances of the buildings, as well as the quality of the satellite/aerial images. Many existing rooftop extraction methods use rooftop corners as a basic component. Nonetheless, existing rooftop corner detectors either suffer from high missed detection or introduce high false alarm. Based on the observation that rooftop corners are typically of L-shape, we propose an L-shaped corner detector for automatic rooftop extraction from high resolution satellite/aerial imagery. The proposed detector considers information in a spatial circle around each pixel to construct a feature map which captures the probability of L-shaped corner at every pixel. Our experimental results on a rooftop database of over 200 buildings demonstrate its effectiveness for detecting rooftop corners. Furthermore, our proposed detector is complementary to many existing rooftop extraction approaches which require reliable rooftop corners as their inputs. For instance, it can be used in the quadrilateral footprint extraction methods or in driving level-set-based segmentation techniques.

Paper Details

Date Published: 15 October 2015
PDF: 7 pages
Proc. SPIE 9643, Image and Signal Processing for Remote Sensing XXI, 964318 (15 October 2015); doi: 10.1117/12.2194279
Show Author Affiliations
Hui Li Tan, Institute for Infocomm Research (Singapore)
Jiayuan Fan, Institute for Infocomm Research (Singapore)
Shijian Lu, Institute for Infocomm Research (Singapore)


Published in SPIE Proceedings Vol. 9643:
Image and Signal Processing for Remote Sensing XXI
Lorenzo Bruzzone, Editor(s)

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