| Publisher | Reed Elsevier | ||
|---|---|---|---|
| Format | 453.7KB PDF | Date added | 13 Nov 2003 |
| Topics | Biometrics | ||
| Downloads | 203 | ||
A biometric authentication system operates by acquiring biometric data from a user and comparing it against the template data stored in a database in order to identify a person or to verify a claimed identity. Most systems store multiple templates per user in order to account for variations observed in a person's biometric data. This paper proposes two methods to perform automatic template selection where the goal is to select prototype fingerprint templates for a finger from a given set of fingerprint impressions. The first method, called DEND, employs a clustering strategy to choose a template set that best represents the intra-class variations, while the second method, called MDIST, selects templates that exhibit maximum similarity with the rest of the impressions.
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