Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
535536 | Pattern Recognition Letters | 2005 | 12 Pages |
Abstract
A novel adapted strategy for combining general and user-dependent knowledge at the decision level in multimodal biometric authentication is presented. User-independent, user-dependent, and adapted fusion and decision schemes are compared by using a bimodal system based on fingerprint and written signature. The adapted approach is shown to outperform the other strategies considered in this paper. Exploiting available information for training the fusion function is also shown to be better than using existing information for post-fusion trained decisions.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Julian Fierrez-Aguilar, Daniel Garcia-Romero, Javier Ortega-Garcia, Joaquin Gonzalez-Rodriguez,