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Image retrieval with binary hamming distance
CReSTIC, Université de Reims-Champagne-Ardenne, I.U.T, Troyes, France.ORCID iD: 0000-0002-9999-9197
LE2I, Université de Bourgogne, I.U.T., Le Creusot, France.
2007 (English)In: VISAPP 2007 - 2nd International Conference on Computer Vision Theory and Applications, Proceedings, 2007, no MTSV/-, p. 237-240Conference paper, Published paper (Refereed)
Abstract [en]

This article proposes a content-based indexing and retrieval (CBIR) system based on query-by-visual-example using hierarchical binary signatures. Binary signatures are obtained through a described binarization process of classical features (color, texture and shape). The Hamming binary distance (based on binary XOR operation) is used for computing distances. This technique was tested on a real natural image collection containing 10 000 images and on a virtual collection of one million images. Results are very good both in terms of speed and accuracy allowing near real-time image retrieval in very large image collections.

Place, publisher, year, edition, pages
2007. no MTSV/-, p. 237-240
Keywords [en]
Binary signature, Content-based image retrieval, Multiresolution analysis, Binarization, Computing distances, Content-based indexing and retrieval, Large images, Natural images, System-based, XOR operation, Computer vision, Content based retrieval, Hamming distance, Information retrieval
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hj:diva-60443Scopus ID: 2-s2.0-67650257975OAI: oai:DiVA.org:hj-60443DiVA, id: diva2:1759242
Conference
2nd International Conference on Computer Vision Theory and Applications, VISAPP 2007, 8-11 March 2007, Barcelona, Spain
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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