- Title
- A multi-biometric feature-fusion framework for improved uni-modal and multi-modal human identification
- Creator
- Brown, Dane L, Bradshaw, Karen L
- Subject
- To be catalogued
- Date
- 2016
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/473696
- Identifier
- vital:77673
- Identifier
- xlink:href="https://ieeexplore.ieee.org/abstract/document/7568927"
- Description
- The lack of multi-biometric fusion guidelines at the feature-level are addressed in this work. A feature-fusion framework is geared toward improving human identification accuracy for both single and multiple biometrics. The foundation of the framework is the improvement over a state-of-the-art uni-modal biometric verification system, which is extended into a multi-modal identification system. A novel multi-biometric system is thus designed based on the framework, which serves as fusion guidelines for multi-biometric applications that fuse at the feature-level. This framework was applied to the face and fingerprint to achieve a 91.11% recognition accuracy when using only a single training sample. Furthermore, an accuracy of 99.69% was achieved when using five training samples.
- Format
- computer, online resource, application/pdf, 1 online resource (5 pages), pdf
- Publisher
- IEEE Xplore
- Language
- English
- Relation
- IEEE Symposium on technologies for homeland security (HST), Brown, D. and Bradshaw, K., 2016, May. A multi-biometric feature-fusion framework for improved uni-modal and multi-modal human identification. In 2016 IEEE Symposium on technologies for homeland security (HST) (pp. 1-6). IEEE, IEEE Symposium on technologies for homeland security (HST) p. 1 2016
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of the IEEE Xplore Terms of Use Statement (https://ieeexplore.ieee.org/Xplorehelp/overview-of-ieee-xplore/terms-of-use)
- Rights
- Closed Access
- Hits: 17
- Visitors: 19
- Downloads: 6
Collections
Brown, Dane Lesley (Associate Prof)
SDG 09. Industry, Innovation and Infrastructure
RU Department of Computer Science
Bradshaw, Karen Lee (Assoc Prof)
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | A multi-biometric feature-fusion framework for improved uni-modal and multi-modal human identification.pdf | 625 KB | Adobe Acrobat PDF | View Details Download |