10.5281/zenodo.1088462
https://zenodo.org/records/1088462
oai:zenodo.org:1088462
Anouar Ben Khalifa
Anouar Ben Khalifa
Sami Gazzah
Sami Gazzah
Najoua Essoukri BenAmara
Najoua Essoukri BenAmara
Adaptive Score Normalization: A Novel Approach for Multimodal Biometric Systems
Zenodo
2013
Multibiometrics
Fusion
Score level
Score normalization
Adaptive normalization.
2013-09-02
eng
10.5281/zenodo.1088461
https://zenodo.org/communities/waset
17136
Creative Commons Attribution 4.0 International
Multimodal biometric systems integrate the data presented by multiple biometric sources, hence offering a better performance than the systems based on a single biometric modality. Although the coupling of biometric systems can be done at different levels, the fusion at the scores level is the most common since it has been proven effective than the rest of the fusion levels. However, the scores from different modalities are generally heterogeneous. A step of normalizing the scores is needed to transform these scores into a common domain before combining them. In this paper, we study the performance of several normalization techniques with various fusion methods in a context relating to the merger of three unimodal systems based on the face, the palmprint and the fingerprint. We also propose a new adaptive normalization method that takes into account the distribution of client scores and impostor scores. Experiments conducted on a database of 100 people show that the performances of a multimodal system depend on the choice of the normalization method and the fusion technique. The proposed normalization method has given the best results.