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dc.contributor.authorKaggwa, Fred
dc.contributor.authorNgubiri, John
dc.contributor.authorTushabe, Florence
dc.date.accessioned2021-05-21T07:27:26Z
dc.date.available2021-05-21T07:27:26Z
dc.date.issued2014
dc.identifier.citationKaggwa, F., Ngubiri, J., & Tushabe, F. (2014, June). Evaluation of multiple enrollment for fingerprint recognition. In 2014 Global Summit on Computer & Information Technology (GSCIT) (pp. 1-6). IEEE.en_US
dc.identifier.urihttp://ir.must.ac.ug/xmlui/handle/123456789/827
dc.description.abstractAbstract— Fusion of multiple impressions resulting from multiple fingerprint enrollments is one of the ways often used to improve fingerprint recognition performance. In this research, we perform an evaluation of the effectiveness of using multiple enrollment in fingerprint recognition systems. We design a multiple enrollment algorithm and use it together with existing fingerprint recognition techniques to carry out the evaluation. Our experimentation results and evaluations show that multiple enrollment as whole outperforms single enrollment. Multiple enrollment in experiment (1) improved the recognition performance by 83% from EER1 of 0.75% to EER of 0.13% with FVC2000-DB2, and by 79% from EER of 1.14% to EER of 0.28% with the SAS-DB2 fingerprint database. On the other hand, the multiple enrollment in experiment (2) improved the recognition performance by 71% from EER of 6.14% to EER of 1.75% with FVC2000-DB2 and improved recognition performance by 53% from EER of 14.97% to EER of 6.94% with SAS-DB2 fingerprint database.en_US
dc.language.isoen_USen_US
dc.publisherGlobal Summit on Computer & Information Technologyen_US
dc.subjectMultiple enrollmenten_US
dc.subjectSingle enrollmenten_US
dc.subjectRecognition Performance Improvementen_US
dc.subjectTraditional Minutiae-based matchingen_US
dc.subjectSpectral Minutiae-based matchingen_US
dc.titleEvaluation of Multiple Enrollment for Fingerprint Recognition.en_US
dc.typeArticleen_US


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