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Dimension Reduction of Hand and Face Feature Level Fusion in Multimodal Biometric Authentication
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
The proposed work is a multimodal biometric authentication approach with image texture feature dimension reduction of trained feature vector which leads reduction in memory size and in turn reduces the computational time. In this paper hand and face features are used for person identification. The texture features of hand image are extracted using Haar and several Daubechie's of 2D-DWT followed by 2D- edge detector gives better identification with reduction in feature vector and face features
doi:10.35940/ijitee.i8924.078919
fatcat:o7y2zkeztnbbrfnut5kjmvzn3m