An Efficient Secure Multimodal Biometric Fusion Using Palmprint and Face Image

TL;DR

This paper presents a secure multimodal biometric authentication system combining face and palmprint recognition, enhancing robustness and accuracy through score-level fusion for improved personal identification.

Contribution

It introduces a novel multimodal biometric system that fuses face and palmprint features at the matching score level, improving recognition performance and robustness.

Findings

Enhanced recognition accuracy over single modality systems

Robustness against biometric spoofing or failure

Effective fusion at score level improves decision reliability

Abstract

Biometrics based personal identification is regarded as an effective method for automatically recognizing, with a high confidence a person's identity. A multimodal biometric systems consolidate the evidence presented by multiple biometric sources and typically better recognition performance compare to system based on a single biometric modality. This paper proposes an authentication method for a multimodal biometric system identification using two traits i.e. face and palmprint. The proposed system is designed for application where the training data contains a face and palmprint. Integrating the palmprint and face features increases robustness of the person authentication. The final decision is made by fusion at matching score level architecture in which features vectors are created independently for query measures and are then compared to the enrolment template, which are stored during database preparation. Multimodal biometric system is developed through fusion of face and palmprint recognition.