Multimodal biometric system based on decision level fusion

A Biometric Framework is one of the crucial Pattern Recognition Framework that are utilized for recognizing individuals utilizing distinctive Biometric Characteristics. The Authentication System design using single modality may not fulfill the prerequisite of requesting applications in term of properties, for example, Accuracy, Acceptability and Performances. Due to its limitations, Multimodal Biometrics has been introduced where fusion of the modalities is the bigger challenge. Multimodal Biometric Framework is utilized as productive biometric framework which is a combination of two or more biometric attributes to upgrade the security. In Multimodal Biometrics, Fusion can be performed on different levels. In this paper, Fusion at decision level is implemented where different decision level fusion techniques have been tested on the Iris and Fingerprint samples on standard dataset and performance of the system is measured on the basis of False Acceptance Rate (FAR), False Rejection Rate (FRR) and Recoginition Accuracy.