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dc.contributor.authorHoyle, Kevinen_US
dc.date.accessioned2014-03-14T20:41:27Z
dc.date.available2014-03-14T20:41:27Z
dc.date.issued2011-07-06en_US
dc.identifier.otheretd-07142011-112818en_US
dc.identifier.urihttp://hdl.handle.net/10919/34010
dc.description.abstractIn order to deliver statistical and qualitative backing to latent fingerprint evidence, algorithms are proposed (1) to perform fingerprint matching to aid in quality assessment, and (2) to discover statistically rare features or patterns in fingerprints. These features would help establish an objective minimum-quality baseline for latent prints as well as aid in the latent examination process in making a matching comparison. The proposed methodologies use minutiae triplet-based features in a hierarchical fashion, where not only minutia points are used, but ridge information is used to help establish relations between minutiae. Results show (1) that our triplet-based descriptor is useful in eliminating false matches in the matching algorithm, and (2) that a set of distinctive features can be found that have sufficient discriminatory power to aid in quality assessment.en_US
dc.publisherVirginia Techen_US
dc.relation.haspartHoyle_KE_T_2011.pdfen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectminutiaen_US
dc.subjectsufficiencyen_US
dc.subjectlatenten_US
dc.subjectqualityen_US
dc.subjectfingerprintsen_US
dc.subjectfriction ridgesen_US
dc.subjecttrianglesen_US
dc.subjecttripletsen_US
dc.titleMinutiae Triplet-based Features with Extended Ridge Information for Determining Sufficiency in Fingerprintsen_US
dc.typeThesisen_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
dc.contributor.committeechairHsiao, Michael S.en_US
dc.contributor.committeememberFox, Edward Alanen_US
dc.contributor.committeememberAbbott, A. Lynnen_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-07142011-112818/en_US
dc.date.sdate2011-07-14en_US
dc.date.rdate2011-07-21
dc.date.adate2011-07-21en_US


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