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Privacy Preserving Multimodal Biometrics in Online Passport Recognition

K. Gunasekaran, S. Achutha Priya, D. Saravanan, P. Akilan

Abstract


The biometric recognition systems rely on a single biometric for authentication for a particular user. Unfortunately these systems having some inevitable problems such as Noisy data, Spoof attack, Non-universality etc and hence it is not used in online passport registration system. In order to rectify the noise in the image, a novel joint sparsity based feature level fusion algorithm is used for multimodal biometrics recognition. The multimodal multivariate sparse representation method for multimodal biometrics recognition to test the data by a sparse linear combination of training data. It compares the different modalities of the test subject with the templates stored in DB and recognize the user’s authentication, simultaneously take into an account correlations as well as coupling information between biometric modalities. The particular multivariate authentication can be used for online passport authentication using multiple biometric identification system. Here the finger, face and signature are considered as biometrics parameters. These biometric images can be used for authentication in online passport management system. Besides it secure environment of the passport system recognition.

Keywords


Multimodal, Feature Level Fusion, SVM, Fuzzy C Mean, Kanade-Lucas-Tomasi, Color Code

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References


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