A novel approach for secured multimodal biometric authentication based on data fusion technique Online publication date: Wed, 03-Mar-2021
by Gayatri U. Bokade; Rajendra D. Kanphade
International Journal of Computational Vision and Robotics (IJCVR), Vol. 11, No. 2, 2021
Abstract: The upcoming biometric technology is focusing more on multiple biometric traits to authenticate the user for security, access control and universal identity. This is because utmost considered powerful biometric when used solely, grieves from spoof attacks, intra-class erraticism, noise, vulnerability, etc. In the arena of biometrics, the integration of evidences offered by multiple biometric is considered as an effective mode of enhancing the authentication accuracy and security. This research work proposes an authentication technique for a multimodal biometric scheme using three traits, i.e., face, ear and palmprint at feature level fusion. This novel method utilises the raw data fusion technique to create unique pattern for each registered user. Even with the use of three different biometrics traits, the template is created with extreme low dimension and by using a single algorithm. The proposed system provides security with reduced computational complexity and improved robustness.
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