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A Multimodal Biometeric Integrating Palmprint and Face With Fingerprint


John Christopher, T.Jabarajan


Vol. 10  No. 10  pp. 144-149


This paper deals with a multimodal biometric recognition system integrating palmprint, fingerprint and face based on feature extraction fusion. The feature vectors are extracted independently from the pre-processed images of palmprint, fingerprint and face using a combined Fisher Linear Discriminant (FLD) and Gabor Wavelet responses. Gabor wavelets have properties of being more robust to image illuminations, small translations, limited rotations and having a superior feature representation in both spatial and frequency domains. On the other hand, FLD seeks those projections that are efficient for data discrimination and produces well separated classes in low-dimensional subspaces. This new combined method involves convolving a palmprint, fingerprint and face image with a series of Gabor wavelets at different scales and rotations before extracting features from the resulting Gabor filtered images. Linear discriminant analysis is then applied to the feature vectors for dimension reduction as well as class reparability. The identity established by this system is more reliable than the identity established by individual biometric systems. Integrating multiple biometric traits improves recognition performance and reduces fraudulent access. The proposed multimodal biometric system overcomes the limitations of individual biometric systems and also meets the response time as well as the accuracy requirements.


face recognition, Gabor wavelet, and Fisher linear discriminator