Fusion in Fingerprint Authentication: Two Finger Scenarios
This paper presents our initial results of fingerprint fusion by analysing all pair combinations of ten fingers (i.e. 45 pairs). As a fingerprint verification algorithm we use a commercially available software package from Neurotechnology. As a test data set we use GUC100 multi scanner fingerprint d...
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Published in | 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing pp. 356 - 359 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.10.2010
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Subjects | |
Online Access | Get full text |
ISBN | 1424483786 9781424483785 |
DOI | 10.1109/IIHMSP.2010.93 |
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Abstract | This paper presents our initial results of fingerprint fusion by analysing all pair combinations of ten fingers (i.e. 45 pairs). As a fingerprint verification algorithm we use a commercially available software package from Neurotechnology. As a test data set we use GUC100 multi scanner fingerprint database which contains fingerprint images of all ten fingers from 100 subjects collected over several months. We conduct score level fusion and apply two fusion methods, namely max and sum rules. Our analysis indicates that fusion using both rules provide improvement in all scenarios, and max rule showing slightly better performance compared to max rule's performance. The obtained performance improvements (in terms of EER) for sum and max rules are in the range of 60.2%-91.1% and 67.4%-93.5%, respectively. |
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AbstractList | This paper presents our initial results of fingerprint fusion by analysing all pair combinations of ten fingers (i.e. 45 pairs). As a fingerprint verification algorithm we use a commercially available software package from Neurotechnology. As a test data set we use GUC100 multi scanner fingerprint database which contains fingerprint images of all ten fingers from 100 subjects collected over several months. We conduct score level fusion and apply two fusion methods, namely max and sum rules. Our analysis indicates that fusion using both rules provide improvement in all scenarios, and max rule showing slightly better performance compared to max rule's performance. The obtained performance improvements (in terms of EER) for sum and max rules are in the range of 60.2%-91.1% and 67.4%-93.5%, respectively. |
Author | Bours, P Gafurov, D Bian Yang Busch, C |
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Snippet | This paper presents our initial results of fingerprint fusion by analysing all pair combinations of ten fingers (i.e. 45 pairs). As a fingerprint verification... |
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StartPage | 356 |
SubjectTerms | Fingerprint recognition Fingers Indexes ISO standards Magnetic resonance Thumb |
Title | Fusion in Fingerprint Authentication: Two Finger Scenarios |
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