DocumentCode :
1763219
Title :
Template-Based Hierarchical Building Extraction
Author :
Sellaouti, Aymen ; Hamouda, A. ; Deruyver, Aline ; Wemmert, Cedric
Author_Institution :
Lab. of Comput. in Program., Algorithmic & Heuristic, Campus Univ. Tunis, Tunis, Tunisia
Volume :
11
Issue :
3
fYear :
2014
fDate :
41699
Firstpage :
706
Lastpage :
710
Abstract :
Automatic building extraction is an important field of research in remote sensing. This letter introduces a new object-based building extraction approach. So far, many object-based algorithms for building extraction have been proposed. However, these algorithms mainly operate in two phases: object construction and building extraction. The majority of these algorithms heavily relies on the object construction process, mainly due to the lack of interaction between the two steps. To overcome these drawbacks, we introduce a new hierarchical approach based on building templates. Carried out experiments on data sets of images from the urban area of Strasbourg show the benefits of our approach.
Keywords :
buildings (structures); feature extraction; geophysical image processing; object recognition; remote sensing; automatic building extraction; building template; hierarchical approach; object construction; remote sensing; template based hierarchical building extraction; Buildings; Data mining; Feature extraction; Image resolution; Image segmentation; Remote sensing; Shape; Building; cooperation; dynamic template; object-based;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
Publisher :
ieee
ISSN :
1545-598X
Type :
jour
DOI :
10.1109/LGRS.2013.2276936
Filename :
6587110
Link To Document :
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