Score Level Fusion Based Personal Authentication Using Fingerprint and Speech
نویسندگان
چکیده
In this paper development of a multimodal based biometric fusion system is discussed. A fingerprint recognition system is developed using global singularity features. Mel-frequency Cepstral Coefficients are used to recognise a speaker using the backpropagation artificial neural network. A score level fusion based recognition system is developed using fingerprint and speech match scores and the equal error rate (EER) measured shows a good improvement with 100% recognition rate is obtained for over a large span of match score threshold.
منابع مشابه
Multifinger Feature Level Fusion Based Fingerprint
Fingerprint based authentication systems are one of the cost-effective biometric authentication techniques employed for personal identification. As the data base population increases, fast identification/recognition algorithms are required with high accuracy. Accuracy can be increased using multimodal evidences collected by multiple biometric traits. In this work, consecutive fingerprint images...
متن کاملAuthentication Using Multimodal Biometric Features
Multimodal biometric systems is the consolidated multiple biometric sources, which enable the recognition performance better than the single biometric modality systems. The information fusion in a multimodal system can be performed at various levels like data level fusion, feature level fusion, match score level fusion and decision level fusion. In this paper, we have studied the performance of...
متن کاملScore Selection Techniques for Fingerprint Multi-modal Biometric Authentication
Fingerprints are one of the most used biometrics for automatic personal authentication. Unfortunately, it is often difficult to design fingerprint matchers exhibiting the performances required in real applications. To meet the application requirements, fusion techniques based on multiple matching algorithms, multiple fingerprints, and multiple impressions of the same fingerprint, have been inve...
متن کاملP.k. Mahesh and M.n. Shanmukha Swamy: Fusing Speech Signal and Palmprint Features for an Secured Authentication System
In the application of Biometric authentication, personal identification is regarded as an effective method for automatic recognition, with a high confidence, a person’s identity. Using multimodal biometric systems we typically get better performance compare to single biometric modality. This paper proposes the multimodal biometrics system for identity verification using two traits, i.e., speech...
متن کاملAnalysis of Bipartite Rankboost Approach for Score Level Fusion of Face and Palmprint Biometrics
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 ...
متن کامل