0000000000928663

AUTHOR

Jérôme Landré

0000-0002-9999-9197

showing 2 related works from this author

Analyse multirésolution pour la recherche et l'indexation d'images par le contenu dans les bases de données images - Application à la base d'images p…

2005

Recent content-based image retrieval systems offer an interactive visual browsing of images databases. These methods perform a classification of images (offline) into a search tree for users browsing (online). This approach shows three main problems:1) The size of decriptor vector (n>100) makes distance computing sensitive to dimensionality curse,2) Having many different kinds of attributes into descriptor vector does not help classification,3) In general, classification does not take in consideration users' search context. In this work, we propose a method based on building hierarchical signatures having small increasing sizes, this allows to take users' search context into consideration. …

hierarchical organisationanalyse multirésolutionpsycho-visual browsingindexation par le contenumultiresolution analysiscontent-based image indexing and retrievalimages databaseclassificationarbre de recherche flou.[ INFO.INFO-HC ] Computer Science [cs]/Human-Computer Interaction [cs.HC]arbre de recherche flou[INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC][INFO.INFO-HC] Computer Science [cs]/Human-Computer Interaction [cs.HC]fuzzy search tree.base d'imagesnavigation psycho-visuelleorganisation hiérarchique
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Automatic building of a visual interface for content-based multiresolution retrieval of paleontology images

2001

In this article we present research work in the field of content-based image retrieval in large databases applied to the paleontology image database of the Universite´ de Bourgogne, Dijon, France, called ‘‘TRANS’TYFIPAL.’’ Our indexing method is based on multiresolution decomposition of database images using wavelets. For each family of paleontology images we try to find a model image that represents it. The K-means automatic classification algorithm divides the space of parameters into several clusters. A model image for each cluster is computed from the wavelet transform of each image of the cluster. Then a search tree is built to offer users a graphic interface for retrieving images. So …

Information retrievalContextual image classificationComputer sciencebusiness.industrySearch engine indexingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION020206 networking & telecommunicationsImage processing02 engineering and technologyContent-based image retrievalAtomic and Molecular Physics and OpticsSearch treeComputer Science ApplicationsPaleontologyAutomatic image annotation[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionVisual WordArtificial intelligenceElectrical and Electronic EngineeringbusinessImage retrievalComputingMilieux_MISCELLANEOUS
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