Abstract
In the biometric verification system of a smart gun, the rightful user of a gun is recognized based on grip-pattern recognition. It was found that the verification performance of this system degrades strongly when the data for training and testing have been recorded in different sessions with a time lapse. This is due to the variations between the probe image and the gallery image of a subject. In this work the grip-pattern verification has been implemented based on both classifiers of the likelihood-ratio classifier and the support vector machine. It has been shown that the support vector machine gives much better results than the likelihood-ratio classifier if there are considerable variations between data for training and testing. However, once the variations are reduced by certain techniques and thus the data are better modelled during the training process, the support vector machine tends to lose its superiority.
Original language | English |
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Title of host publication | Image and Signal Processing |
Subtitle of host publication | 3rd International Conference, ICISP 2008. Cherbourg-Octeville, France, July 1-3, 2008. Proceedings |
Place of Publication | Berlin |
Publisher | Springer |
Pages | 289-295 |
Number of pages | 7 |
ISBN (Print) | 978-3-540-69904-0 |
DOIs | |
Publication status | Published - 6 Jul 2008 |
Event | 3rd International Conference on Image and Signal Processing, ICISP 2008 - Cherbourg-Octeville, France Duration: 1 Jul 2008 → 3 Jul 2008 Conference number: 3 |
Publication series
Name | Lecture Notes in Computer Science |
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Publisher | Springer Verlag |
Volume | 5099 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 3rd International Conference on Image and Signal Processing, ICISP 2008 |
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Abbreviated title | ICISP |
Country/Territory | France |
City | Cherbourg-Octeville |
Period | 1/07/08 → 3/07/08 |
Keywords
- EWI-14299
- CR-I.5
- IR-62576
- METIS-254945
- SCS-Safety