The week's pick
Reseach Article
Feature Level Fusion the Performance of Multimodal Biometric Systems
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 123 - Number 11 |
| Year of Publication: 2015 |
| Authors: Harbi AlMahafzah, Ma'en Zaid AlRawashdeh |
10.5120/ijca2015905600
|
Harbi AlMahafzah, Ma'en Zaid AlRawashdeh . Feature Level Fusion the Performance of Multimodal Biometric Systems. International Journal of Computer Applications. 123, 11 ( August 2015), 37-43. DOI=10.5120/ijca2015905600
Abstract
This paper proposed the use of multimodal feature-level fusion to prove the improvement performance of multimodal authentication. Different algorithm used for features extraction, LG for extracting FKP features, LPQ for iris and Palmprint features extraction, and PCA for extracting face features. Results brought to light that the multimodal authentication process gained higher performance than single modality. The biometric performance using feature-level fusions under “Z-score”, “Tanh”, “Median”, and Min-Max normalization has been demonstrated in this paper.
References
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