The week's pick
Reseach Article
Performance Enhancement in Multimodal Biometrics for Authentication
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 183 - Number 25 |
| Year of Publication: 2021 |
| Authors: Dharun Surath K.S., R. Venkatesan |
10.5120/ijca2021921634
|
Dharun Surath K.S., R. Venkatesan . Performance Enhancement in Multimodal Biometrics for Authentication. International Journal of Computer Applications. 183, 25 ( Sep 2021), 41-44. DOI=10.5120/ijca2021921634
Abstract
The biometric system used for person identification is based on the physical modality such as fingerprint, iris, face, etc for providing security to the information. Normally, when a single modality is used for authentication or for encryption there might be a security issue if the hacker or intruder identifies the single modality. To overcome this issue, the proposed work uses multimodal system which combines fingerprint and iris biometrics for improving the security of the information. This Multimodal Biometrics in Information Security is done by extracting the feature points from the fingerprint and iris of the individual, followed by performing fusion of the biometric features and encrypting the fused matrix using Advanced Encryption Standards (AES) which could be used as a key for the authentication of an individual. In this paper, a new fusion technique namely modified-Canonical Correlation Analysis (m-CCA) has been proposed for fusion. The proposed method’s performance is evaluated by constructing the confusion matrix and extracting the Genuine Acceptance Rate (GAR), which is observed to be performing better.
References
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