Toward a higher-level visual representation ...
Document type :
Article dans une revue scientifique
Title :
Toward a higher-level visual representation for content-based image retrieval
Author(s) :
Elsayad, Ismail [Auteur]
FOX MIIRE [LIFL]
Martinet, Jean [Auteur]
FOX MIIRE [LIFL]
Urruty, Thierry [Auteur]
SIC [XLIM-SIC]
Djeraba, Chaabane [Auteur]
FOX MIIRE [LIFL]
FOX MIIRE [LIFL]
Martinet, Jean [Auteur]
FOX MIIRE [LIFL]
Urruty, Thierry [Auteur]
SIC [XLIM-SIC]
Djeraba, Chaabane [Auteur]

FOX MIIRE [LIFL]
Journal title :
Multimedia Tools and Applications
Pages :
455-482
Publisher :
Springer Verlag
Publication date :
2012
ISSN :
1380-7501
HAL domain(s) :
Informatique [cs]/Recherche d'information [cs.IR]
Informatique [cs]/Traitement des images [eess.IV]
Informatique [cs]/Traitement des images [eess.IV]
English abstract : [en]
Having effective methods to access the desired images is essential nowadays with the availability of a huge amount of digital images. The proposed approach is based on an analogy between content-based image retrieval and ...
Show more >Having effective methods to access the desired images is essential nowadays with the availability of a huge amount of digital images. The proposed approach is based on an analogy between content-based image retrieval and text retrieval. The aim of the approach is to build a meaningful mid-level representation of images to be used later on for matching between a query image and other images in the desired database. The approach is based firstly on constructing different visual words using local patch extraction and fusion of descriptors. Secondly, we introduce a new method using multilayer pLSA to eliminate the noisiest words generated by the vocabulary building process. Thirdly, a new spatial weighting scheme is introduced that consists of weighting visual words according to the probability of each visual word to belong to each of the n Gaussian. Finally, we construct visual phrases from groups of visual words that are involved in strong association rules. Experimental results show that our approach outperforms the results of traditional image retrieval techniques.Show less >
Show more >Having effective methods to access the desired images is essential nowadays with the availability of a huge amount of digital images. The proposed approach is based on an analogy between content-based image retrieval and text retrieval. The aim of the approach is to build a meaningful mid-level representation of images to be used later on for matching between a query image and other images in the desired database. The approach is based firstly on constructing different visual words using local patch extraction and fusion of descriptors. Secondly, we introduce a new method using multilayer pLSA to eliminate the noisiest words generated by the vocabulary building process. Thirdly, a new spatial weighting scheme is introduced that consists of weighting visual words according to the probability of each visual word to belong to each of the n Gaussian. Finally, we construct visual phrases from groups of visual words that are involved in strong association rules. Experimental results show that our approach outperforms the results of traditional image retrieval techniques.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :
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