Building change detection from uniform regions

Charles Beumier, Mahamadou Idrissa

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdragepeer review

Samenvatting

This paper deals with building change detection by supervised classification of image regions into 'built' and 'non-built' areas. Regions are the connected components of low gradient values in a multi-spectral aerial image. Classes are learnt from spectral (colour, vegetation index) and elevation cues relatively to building polygons and non building areas as defined in the existing database. Possible candidate building regions are then filtered by geometrical features. Inconsistencies in the database with the recent image are automatically detected. Tests in cooperation with the Belgian National Geographical Institute on an area with sufficient buildings and landscape variety have shown that the system allows for the effective verification of unchanged buildings, and detection of destructions and new candidate buildings.

Originele taal-2Engels
TitelProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings
Pagina's648-655
Aantal pagina's8
DOI's
StatusGepubliceerd - 2012
Evenement17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012 - Buenos Aires, Argentinië
Duur: 3 sep. 20126 sep. 2012

Publicatie series

NaamLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7441 LNCS
ISSN van geprinte versie0302-9743
ISSN van elektronische versie1611-3349

Congres

Congres17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012
Land/RegioArgentinië
StadBuenos Aires
Periode3/09/126/09/12

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