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Sensors 2015, 15(2), 3172-3203; doi:10.3390/s150203172

Building Roof Segmentation from Aerial Images Using a Lineand Region-Based Watershed Segmentation Technique

1
IRTES-SeT, University of Technology of Belfort-Montbeliard, 13 rue Ernest-Thierry Mieg, 90010 Belfort cedex, France
2
LASTID Laboratory, Département de Physique, Faculté des Sciences, Université Ibn Tofail, B.P 133, 14000 Kénitra, Maroc
3
Univ Lille Nord de France, F-59000 Lille, IFSTTAR, LEOST, F59650 Villeneuve d'Ascq, France
4
National School of Applied Sciences of Tangier (ENSAT), Abdemalek Essaadi University, B.P. 1818, 90000 Tangier, Maroc
*
Author to whom correspondence should be addressed.
Received: 18 November 2014 / Revised: 9 December 2014 / Accepted: 20 January 2015 / Published: 2 February 2015
(This article belongs to the Section Remote Sensors)

Abstract

In this paper, we present a novel strategy for roof segmentation from aerial images (orthophotoplans) based on the cooperation of edge- and region-based segmentation methods. The proposed strategy is composed of three major steps. The first one, called the pre-processing step, consists of simplifying the acquired image with an appropriate couple of invariant and gradient, optimized for the application, in order to limit illumination changes (shadows, brightness, etc.) affecting the images. The second step is composed of two main parallel treatments: on the one hand, the simplified image is segmented by watershed regions. Even if the first segmentation of this step provides good results in general, the image is often over-segmented. To alleviate this problem, an efficient region merging strategy adapted to the orthophotoplan particularities, with a 2D modeling of roof ridges technique, is applied. On the other hand, the simplified image is segmented by watershed lines. The third step consists of integrating both watershed segmentation strategies into a single cooperative segmentation scheme in order to achieve satisfactory segmentation results. Tests have been performed on orthophotoplans containing 100 roofs with varying complexity, and the results are evaluated with the VINETcriterion using ground-truth image segmentation. A comparison with five popular segmentation techniques of the literature demonstrates the effectiveness and the reliability of the proposed approach. Indeed, we obtain a good segmentation rate of 96% with the proposed method compared to 87.5% with statistical region merging (SRM), 84% with mean shift, 82% with color structure code (CSC), 80% with efficient graph-based segmentation algorithm (EGBIS) and 71% with JSEG. View Full-Text
Keywords: orthophotoplan; image segmentation; watershed; region merging; roof segmentation; 2D roof ridge modeling orthophotoplan; image segmentation; watershed; region merging; roof segmentation; 2D roof ridge modeling
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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MDPI and ACS Style

El Merabet, Y.; Meurie, C.; Ruichek, Y.; Sbihi, A.; Touahni, R. Building Roof Segmentation from Aerial Images Using a Lineand Region-Based Watershed Segmentation Technique. Sensors 2015, 15, 3172-3203.

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