Identification of Individual Using Voice and Fingerprint
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Individual identification using biometric is gaining more and more attention. It has been shown that combining different biometric modalities increases the robustness and enables to achieve better performances than single modality. In this context, this paper presents an effective method to combine voice and fingerprint features for biometric authentication. For each task, up-to-date methods are analyzed. Based on the analysis, an integrated solution for speech and fingerprint recognition is developed.
The extracted features are used to form input matrix which is stored as a database. For feature extraction we have used matlab toolbox and image processing toolbox. For recognition and verification of purpose we have used neural network toolbox.
Main aim is to design individual identification system which can be used for detecting right person. The experimental results are consistent with the available database.
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