A classification-matching combination for image retrieval.
Nowadays, applications dealing with information extracted from images are commonplace. The widespread use of multimedia information (images, video, audio etc.) makes necessary applications capable of storing, and therefore retrieving, it. Information extracted from images is usually complex and high...
| Publicado en: | Online & CD-Rom Review Vol. 23; no. 1; pp. 11 - 19 |
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| Autores principales: | , , |
| Formato: | tables/charts Journal Article |
| Publicado: |
Emerald Publishing Limited
1999 Feb
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=107185669&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 107185669 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13532642 2OK jtl: Online & CD-Rom Review issn: 13532642 maglogo: N pubinfo: dt: 1999 Feb vid: 23 iid: 1 pid: 465 pub: Emerald Publishing Limited artinfo: ui: 107185669 107185669 1999037453 10.1108/14684529910334038 107185669 ppf: 11 ppct: 8 formats: tig: atl: A classification-matching combination for image retrieval. aug: au: Encinas J Llorens J de Miguel A affil: GTI (Information Technology Group), Computer Science Department, Carlos III University, Madrid, Spain. E-mail: juliom@gti.uc3m.es sug: subj: Information Retrieval Multimedia Image Processing, Computer Assisted Software Abstracting and Indexing Information Retrieval Methods ab: Nowadays, applications dealing with information extracted from images are commonplace. The widespread use of multimedia information (images, video, audio etc.) makes necessary applications capable of storing, and therefore retrieving, it. Information extracted from images is usually complex and high dimensional. The extraction of non-textual low-level indexing features from images is now a research field, and this process principally suffers because of the computational cost of the high dimensionality of those features. A new way to classify and match low-level features extracted from images, for retrieval purposes, is presented in this paper. M-tree and R-tree structures are used, as well as an incremental version of the k-means classification algorithm. This set of algorithms is used to solve the problem of low performance when retrieving previously catalogued images. pubtype: Academic Journal doctype: tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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