Supreetha Gowda, H. D. and Hemantha Kumar, G. and Imran, Mohammad (2018) Multi-modal biometric system on various levels of fusion using LPQ features. Journal of Information and Optimization Sciences, 39 (1). pp. 169-181. ISSN 2169-0103
Full text not available from this repository. (Request a copy)Abstract
In the proposed multimodal biometric verification system, the system is implemented on all levels of fusion strategies (i) fusion prior to matching (sensor level and feature level) and (ii) fusion post matching (score level and decision level), a binding required and a deserving step that outputs a reliable and robust biometric identification and verification systems. We have chosen benchmark databases for our experimentation and considered physiological modalities such as face, palmprint, finger knuckle print, handvein. The performance measures considered here are FAR (False Acceptance Rate) and FRR (False Rejection Rate). Extracting texture features from a well-known texture operator-LPQ (local phase quantization), we have performed sensor level fusion adopting HAAR wavelets, feature level fusion using Z-Score normalization, score level fusion employing simple sum rule and decision level fusion with AND rule. For the implemented biometric recognition system, score level fusion strategy outer performs than the other fusion techniques in terms of EER, yielding good verification rate on all benchmark threshold values (0.01%, 0.1%, 1%), with the GAR=100% at 1% FAR. The tabulated results of the experiments are visualized by BAR chart
| Item Type: | Article |
|---|---|
| Subjects: | D Physical Science > Computer Science |
| Divisions: | Department of > Computer Science |
| Depositing User: | Manjula P Library Assistant |
| Date Deposited: | 13 Aug 2019 06:12 |
| Last Modified: | 13 Aug 2019 06:12 |
| URI: | http://eprints.uni-mysore.ac.in/id/eprint/6309 |
Actions (login required)
 |
View Item |
