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Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/1074

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dc.contributor.authorGanotra, Dinesh-
dc.contributor.authorJoseph, Joby-
dc.contributor.authorSingh, Kehar-
dc.date.accessioned2005-12-30T04:24:10Z-
dc.date.available2005-12-30T04:24:10Z-
dc.date.issued2002-
dc.identifier.citationOptics Communications, 209(4-6), 291-301en
dc.identifier.urihttp://eprint.iitd.ac.in/dspace/handle/2074/1074-
dc.description.abstractNeural networks have been used to carryout calibration process in fringe projection profilometry for the measurement of three-dimensional object shape. The calibration procedure uses several calibration planes whose positions in space are known. Radial basis function based networks and multi-layer perceptron networks are investigated for the phase recovery. Preliminary studies are also presented for the direct reconstruction of the object without the use of the intermediate step of phase plane calculations. Experimental results are presented for diffuse objects.en
dc.format.extent533406 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoenen
dc.subjectNeural networksen
dc.subjectProfilometryen
dc.subject3-D shape measurementen
dc.subjectPhase measurementen
dc.titleProfilometry for the measurement of three-dimensional object shape using radial basis function, and multi-layer perceptron neural networksen
dc.typeArticleen
Appears in Collections:Physics

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