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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Arif, M. Brouard, T. Vincent, N. |
| Copyright Year | 2006 |
| Description | Author affiliation: KRL, Rawalpindi (Arif, M.) |
| Abstract | A new methodology for the person identification and verification using hand features is presented. The features are extracted from gray level hand images, which are scanned by an ordinary commercial scanner. Contrary to other bimodal biometric systems, the palmprint and hand geometry features are acquired from the same image. On their individual performances, these features are grouped into four different feature vectors. A k-NN classifier based on majority vote rule and distance-weighted rule is employed to establish four classifiers. Dempster-Shafer evidence theory is then used to combine these classifiers in case of identification. Besides, for verification step a simple majority rule was found robust for our system. Dempster-Shafer theory has proved to be much more efficient than fusion by others methods like majority vote rule and Borda count method |
| Sponsorship | IEEE Islamabad Sect. Mohammed Ali Jinnah Univ. Pakistan Inst. of Eng. & Appl. Sci |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 2930583 |
| Page Count | 6 |
| File Format | |
| ISBN | 1424404568 |
| DOI | 10.1109/ICEIS.2006.1703170 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-04-22 |
| Publisher Place | Pakistan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Geometry Biometrics Iris Image recognition Shape Voting Fingers Fingerprint recognition Feature extraction Tellurium |
| Content Type | Text |
| Resource Type | Article |
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