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Mostrar registro sencillo 2004-03-26T18:25:08Z 2004-03-26T03:00:00Z 2001
dc.description.abstract The algorithmical architecture and structure is presented for the parallelization of image similarity analysis, based on obtaining multiple digital signatures for each image, in which each "signature" is composed by the most representative coefficients of the wavelet transform of the corresponding image area. In the present paper, image representation by wavelet transform coefficients is analyzed, as well as the convenience/necessity of using multiple coefficients for the study of similarity of images which may have transferred components, with change of sizes, color or texture. The complexity of the involved computation justifies parallelization, and the suggested solution constitutes a combination of a multiprocessors "pipelining", being each of them an homogeneous parallel architecture which obtains signature coefficients (wavelet). Partial reusability of computations for successive signatures makes these architectures pipelining compulsory. en
dc.format.extent 11 p. es
dc.language en es
dc.title Parallelization of image similarity analysis en
dc.type Articulo es
sedici.identifier.uri es
sedici.creator.person Naiouf, Marcelo es
sedici.creator.person Tarrío, Diego F. es
sedici.creator.person De Giusti, Armando Eduardo es
sedici.creator.person De Giusti, Laura Cristina es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
sedici.description.peerReview peer-review es
sedici2003.identifier ARG-UNLP-ART-0000000156 es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 1, no. 5 es
sedici.subject.acmcss98 Parallel algorithms es
sedici.subject.acmcss98 PATTERN RECOGNITION es
sedici.subject.acmcss98 Parallel processors es

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Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)