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Applying matrix decomposition techniques to edge detection operators

dc.contributor.authorSousa, Leonel
dc.contributor.authorSalvado, José
dc.date.accessioned2010-01-14T13:00:46Z
dc.date.available2010-01-14T13:00:46Z
dc.date.issued1998
dc.description.abstractIn this paper decomposition techniques are applied to derivative operators, used for image edge detection. It is shown that the application of decomposition techniques to common edge detectors can result in substantial savings in computing time. For a 25x25 Laplacian of Gaussian, mask, an improvement of six times less arithmetic operations is achieved when decomposition techniques are applied.We also show that these techniques are advantageous for hardware realization of the filters. The memory required to a 2-D (nxn)-th order FIR filter direct realization with distributed arithmetic is O(2(n+1) ) while the worst case for the decomposed filter is O(n x 2n).pt
dc.identifier.citationSOUSA, Leonel; SALVADO, José - Applying matrix decomposition techniques to edge detection operators In Proceedings of RECPAD’98 – 10th Portuguese Conference on Pattern Recognition. Lisboa:APRP, 1998pt
dc.identifier.isbn972-97711-0-3
dc.identifier.urihttp://hdl.handle.net/10400.11/111
dc.language.isoengpt
dc.publisherAPRPpt
dc.subject2-D filterspt
dc.subjectEdge detectionpt
dc.subjectMatrix decompositionpt
dc.subjectComputing efficiencypt
dc.titleApplying matrix decomposition techniques to edge detection operatorspt
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceLisboapt
oaire.citation.title10th Portuguese Conference on Pattern Recognitionpt
person.familyNameSalvado
person.givenNameJosé
person.identifier.ciencia-id5516-036A-CEF1
person.identifier.orcid0000-0002-9839-8015
rcaap.rightsopenAccesspt
rcaap.typeconferenceObjectpt
relation.isAuthorOfPublicationfcdb32be-4575-426c-a450-13ff9fc9ff26
relation.isAuthorOfPublication.latestForDiscoveryfcdb32be-4575-426c-a450-13ff9fc9ff26

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