Feature fusion of palmprint and face via tensor analysis and curvelet transform |
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Authors: | X Xu X Guan D Zhang X Zhang W Deng Z Wang |
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Institution: | 1.School of Electronics and Information Engineering,Xi’an Jiaotong University,Xi’an,People’s Republic of China |
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Abstract: | In order to improve the recognition accuracy of the unimodal biometric system and to address the problem of the small samples
recognition, a multimodal biometric recognition approach based on feature fusion level and curve tensor is proposed in this
paper. The curve tensor approach is an extension of the tensor analysis method based on curvelet coefficients space. We use
two kinds of biometrics: palmprint recognition and face recognition. All image features are extracted by using the curve tensor
algorithm and then the normalized features are combined at the feature fusion level by using several fusion strategies. The
k-nearest neighbour (KNN) classifier is used to determine the final biometric classification. The experimental results demonstrate
that the proposed approach outperforms the unimodal solution and the proposed nearly Gaussian fusion (NGF) strategy has a
better performance than other fusion rules. |
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