Content-based Image Retrieval by Indexing Random Subwindows with Randomized Trees

[en] We propose a new method for content-based image retrieval which exploits the similarity measure and indexing structure of totally randomized tree ensembles induced from a set of subwindows randomly extracted from a sample of images. We also present the possibility of updating the model as new images come in, and the capability of comparing new images using a model previously constructed from a different set of images. The approach is quantitatively evaluated on various types of images and achieves high recognition rates despite its conceptual simplicity and computational efficiency.

Disciplines :

Computer science

Author, co-author :

Marée, Raphaël ; Université de Liège - ULiège > GIGA-Management : Plateforme bioinformatique

Geurts, Pierre ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation

Wehenkel, Louis ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation

Language :

English

Title :

Content-based Image Retrieval by Indexing Random Subwindows with Randomized Trees

Publication date :

30 January 2009

Journal title :

IPSJ Transactions on Computer Vision and Applications

eISSN :

1882-6695

Publisher :

Information Processing Society of Japan, Japan

Special issue title :

Special Issue on ACCV2007

Volume :

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

http://www.jstage.jst.go.jp/article/ipsjtcva/1/0/1_46/_article

Funders :

FEDER - Fonds Européen de Développement Régional [BE]
F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE]
DGTRE - Région wallonne. Direction générale des Technologies, de la Recherche et de l'Énergie [BE]

Commentary :

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Available on ORBi :

since 10 February 2009

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