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A hierarchical architecture for content-based image retrieval of paleontology images
Institut Univ. de Technologie, Le2i, FRE 2309 CNRS, Le Creusot, France.ORCID iD: 0000-0002-9999-9197
Institut Univ. de Technologie, Le2i, FRE 2309 CNRS, Le Creusot, France.
2002 (English)In: Electronic Imaging, 19-25 January 2002: Proceedings volume 4676 / [ed] M. M. Yeung, C.-S. Li & R. W. Lienhart, SPIE - International Society for Optical Engineering, 2002, p. 138-147Conference paper, Published paper (Refereed)
Abstract [en]

In this article a research work in the field of content-based multiresolution indexing and retrieval of images is presented. Our method uses multiresolution decomposition of images using wavelets - in the HSV colorspace - to extract parameters at multiple scales allowing a progressive (coarse-to-fine) retrieval process. Features are automatically classified into several clusters with K-means algorithm. A model image is computed for each cluster in order to represent all the images of this cluster, The process is reiterated again and again and each cluster is sub-divided into sub-clusters. The model images are stored in a tree which is proposed to users for browsing the database. The nodes of the tree are the families and the leaves are the images of the database. A paleontology images database is used to test the proposed technique. This kind of approach permits to build a visual interface easy to use for users. Our main contribution is the building of the tree with multiresolution indexing and retrieval of images and the generation of model images to be proposed to users.

Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2002. p. 138-147
Series
Proceedings of SPIE - The International Society for Optical Engineering, ISSN 0277-786X ; 4676
Keywords [en]
Classification, Content-based image retrieval, Image database, K-means algorithm, Multiresolution analysis, Algorithms, Computer simulation, Database systems, Image analysis, Indexing (of information), Optical resolving power, Web browsers, Multiresolution indexing, Content based retrieval
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hj:diva-60448DOI: 10.1117/12.451084Scopus ID: 2-s2.0-0036029674OAI: oai:DiVA.org:hj-60448DiVA, id: diva2:1759405
Conference
Storage and Retrieval for Media Databases 2002, 23-25 January 2002, San Jose, CA, USA
Available from: 2023-05-25 Created: 2023-05-25 Last updated: 2023-05-25Bibliographically approved

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Landré, Jérôme

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