Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/3601
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dc.contributor.authorTin Tin Aye.en_US
dc.date.accessioned2008-09-17T09:33:16Z-
dc.date.available2008-09-17T09:33:16Z-
dc.date.copyright2003en_US
dc.date.issued2003-
dc.identifier.urihttp://hdl.handle.net/10356/3601-
dc.description.abstractThis dissertation focuses on extraction of minutiae from the gray fingerprint images directly without going through the usual binarization and thinning processes. Multilayer feedforward neural network is used for extraction of minutiae. Two types of most commonly used minutiae, bifurcations and ridge endings, are extracted. If the feature is not bifurcation or ridge ending, we name this image as the 'none' image class.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Biometrics-
dc.titleFingerprint feature extractionen_US
dc.typeThesisen_US
dc.contributor.supervisorSuganthan, Ponnuthurai Nagaratnamen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Computer Control and Automation)en_US
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