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Buildings 2018, 8(5), 65; https://doi.org/10.3390/buildings8050065

Autonomous Building Detection Using Edge Properties and Image Color Invariants

1
National Council for Scientific Research, CNRS, Zahia Salmane street, Jnah, P.O. Box 11-8281 Beirut, Lebanon
2
Department of Computer and Communication Engineering, Islamic University of Lebanon, P.O. Box 30014 Beirut, Lebanon
*
Author to whom correspondence should be addressed.
Received: 20 February 2018 / Revised: 14 April 2018 / Accepted: 18 April 2018 / Published: 1 May 2018
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Abstract

Automated building extraction from high-resolution satellite imagery is a challenging research problem, and several issues remain with respect to the variety of variables to be accounted for. In this paper we present an approach for building detection using multiple cues. We use the shadow, shape, and color features of buildings to propose our approach, known as Building Detection with Shadow Verification (BDSV). BDSV has three main pillars, which are: (1) tile building detection (TBD) to detect roof tile buildings; (2) flat building detection (FBD) to detect non-tile flat buildings according to shape features; and (3) results fusion used to fuse and aggregate results from previous blocks. Analyses performed over different study areas reveal high quality percentage and precision metrics, exceeding 95%. Performance analysis over the SztaKi–Inria and Istanbul datasets shows that BDSV outperforms benchmark algorithms. View Full-Text
Keywords: building extraction; remote sensing; shadow detection; hypothesis and validation; object identification building extraction; remote sensing; shadow detection; hypothesis and validation; object identification
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Ghandour, A.J.; Jezzini, A.A. Autonomous Building Detection Using Edge Properties and Image Color Invariants. Buildings 2018, 8, 65.

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