Building and road extraction on urban VHR IMAGES using SVM combinations and mean shift segmentation

Christophe Simler, Charles Beumier

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdragepeer review

Samenvatting

A method is proposed for building and road detection on very high spatial resolution multispectral aerial image of dense urban areas. First, objects are extracted with a segmentation algorithm in order to use both spectral and spatial information. Second, a spectral-spatial object-level pattern is formed, and then classification is performed using a 3-class SVM classifier, followed by a post-processing using contextual information to handle conflicts. However, in the particular case where many building roofs are grey like the roads and have similar geometry, classification accuracy is inevitably limited. In order to overcome this limitation, different classifiers are combined and different patterns used, improving the accuracy of 10%.

Originele taal-2Engels
TitelVISAPP 2010 - Proceedings of the International Conference on Computer Vision Theory and Applications
Pagina's451-457
Aantal pagina's7
StatusGepubliceerd - 2010
Evenement5th International Conference on Computer Vision Theory and Applications, VISAPP 2010 - Angers, Frankrijk
Duur: 17 mei 201021 mei 2010

Publicatie series

NaamVISAPP 2010 - Proceedings of the International Conference on Computer Vision Theory and Applications
Volume2

Congres

Congres5th International Conference on Computer Vision Theory and Applications, VISAPP 2010
Land/RegioFrankrijk
StadAngers
Periode17/05/1021/05/10

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