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dc.contributor.advisorErdmann, Robert
dc.contributor.authorTobin, Brendan
dc.creatorTobin, Brendanen_US
dc.date.accessioned2013-08-09T19:32:07Z
dc.date.available2013-08-09T19:32:07Z
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/10150/297771
dc.description.abstractMultispectral imaging is an important tool in art conservation because it allows researchers to view under-drawing and restoration efforts on a painting. It is necessary to precisely align various images of the same painting using digital image processing techniques, however this is complicated by inconsistencies in image contents and the use of multiple cameras. This paper seeks to develop an effective method to automatically align and rescale multispectral images of paintings. Key point identification using the Speeded-Up Robust Feature detection algorithm with refinement by Random Sample Consensus fitting was determined to be an accurate and efficient method for aligning visible and infrared multispectral images.
dc.language.isoenen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.titleAutomatic Registration of Multispectral Imagesen_US
dc.typetexten_US
dc.typeElectronic Thesisen_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.levelbachelorsen_US
thesis.degree.disciplineHonors Collegeen_US
thesis.degree.disciplineMaterials Science and Engineeringen_US
thesis.degree.nameB.S.en_US
refterms.dateFOA2018-04-26T12:01:06Z
html.description.abstractMultispectral imaging is an important tool in art conservation because it allows researchers to view under-drawing and restoration efforts on a painting. It is necessary to precisely align various images of the same painting using digital image processing techniques, however this is complicated by inconsistencies in image contents and the use of multiple cameras. This paper seeks to develop an effective method to automatically align and rescale multispectral images of paintings. Key point identification using the Speeded-Up Robust Feature detection algorithm with refinement by Random Sample Consensus fitting was determined to be an accurate and efficient method for aligning visible and infrared multispectral images.


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