Hand Vein Recognition Algorithm Based on NMF with Sparsity and Clustering Property Constraints in Feature Mapping Space

JIA Xu; SUN Fuming; LI Haojie; CAO Yudong

doi:10.1049/cje.2019.06.003

Volume 28 Issue 6

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JIA Xu, SUN Fuming, LI Haojie, et al., “Hand Vein Recognition Algorithm Based on NMF with Sparsity and Clustering Property Constraints in Feature Mapping Space,” Chinese Journal of Electronics, vol. 28, no. 6, pp. 1184-1190, 2019, doi: 10.1049/cje.2019.06.003

Citation:

JIA Xu, SUN Fuming, LI Haojie, et al., “Hand Vein Recognition Algorithm Based on NMF with Sparsity and Clustering Property Constraints in Feature Mapping Space,” Chinese Journal of Electronics, vol. 28, no. 6, pp. 1184-1190, 2019, doi: 10.1049/cje.2019.06.003

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Hand Vein Recognition Algorithm Based on NMF with Sparsity and Clustering Property Constraints in Feature Mapping Space

doi: 10.1049/cje.2019.06.003

1.
School of Electronics and Information Engineering, Liaoning University of Technology, Jinzhou 121001, China;
2.
School of Software Technology, Dalian University of Technology, Dalian 116024, China

Funds: This work is supported by the National Natural Science Foundation of China (No.61502216, No.61572244, No.51679116) and Natural Science Foundation of Liaoning Province (No.2019-ZD-0700).

Received Date: 2018-03-12
Rev Recd Date: 2019-03-05
Publish Date: 2019-11-10

Abstract

Abstract

Most of the existed vein features are lack of robustness to light intensity variation, and some algorithms rely on the specified vein data sets, which leads to the limitation of real applications. To solve the problems, we propose a novel vein recognition algorithm based on Nonnegative matrix factorization (NMF) with double regularization terms. The innovations of our algorithm are mainly reflected in the following two aspects:in order to improve feature robustness, a novel feature mapping function is designed to map the initial Histogram of oriented gradient (HOG) feature to a new space; to enhance the recognition performance, an effective NMF model is presented, which not only reduces feature dimension, but also optimizes the feature sparsity and clustering property simultaneously. Experiments show that the proposed algorithm can achieve satisfactory results in terms of False rejection rate (FRR) and False acceptance rate (FAR), which indicates that our algorithm is valuable for other classification problems.
- Vein recognition,
- Nonnegative matrix factorization (NMF),
- Mapping function,
- Feature sparsity

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References(33)

References

X. Jia, Y.D. Cao, F.M. Sun, et al., "Vein image acquisition method based on quality assessment model without reference", Acta Electronica Sinica, Vol.43, No.2, pp.236-241, 2015. (in Chinese)

X.K. Yan, W.X. Kang, F.Q. Deng, et al., "Palm vein recognition based on multi-sampling and feature-level fusion", Neurocomputing, Vol.151, No.2, pp.798-807, 2015.

C.L. Lin and K.C. Fan, "Biometric verification using thermal images of palm-dorsa vein patterns", IEEE Transactions on Circuits and Systems for Video Technology, Vol.14, No.2, pp.199-213, 2004.

K.J. Wang and Z. Yuan, "Finger vein recognition based on wavelet moment fused with PCA transform", Pattern Recognition and Artificial Intelligence, Vol.20, No.5, pp.692-697, 2007. (in Chinese)

T.G. Liu, Y.X. Wang, X.Y. Li, et al., "Biometric recognition system based on hand vein pattern", Acta Optica Sinica, Vol.29, No.12, pp.3339-3343, 2009. (in Chinese)

T.G. Li, S.L. Ma, Z.B. Zhang, et al., "Hand vein recognition method based on Bandelet transformation", Journal of Jilin University, Vol.45, No.6, pp.975-978, 2007. (in Chinese)

W.Y. Han and J.C. Lee, "Palm vein recognition using adaptive Gabor filter", Expert Systems with Applications, Vol.39, No.18, pp.13225-13234, 2012.

K.Y. Shin, Y.H. Park, D.T. Nguyen, et al., "Finger-vein image enhancement using a fuzzy-based fusion method with gabor and Retinex filtering", Sensors, Vol.14, No.2, pp.3095-3129, 2014.

C.B. Hsu, J.C. Lee, S.S. Hao, et al., "Dorsal hand vein recognition using Gabor feature-based 2-directional 2-dimensional principal component analysis", Advanced Science Letters, Vol.8, pp.813-817, 2012.

R. Wang, G.Y. Wang, Z. Chen, et al., "A palm vein identification system based on Gabor wavelet features", Neural Computing and Applications, Vol.24, No.1, pp.161-168, 2014.

M.A.J. Ali, W. Bu, X.Q. Wu, et al., "Palm vein verification using Gabor filter", International Journal of Computer Science Issues, Vol.10, No.1, pp.678-684, 2013.

J.F. Yang and X. Zhang, "Feature-level fusion of fingerprint and finger-vein for personal identification", Pattern Recognition Letters, Vol.33, No.5, pp.623-628, 2012.

J.C. Lee, C.H. Lee, C.B. Hsu, et al., "Dorsal hand vein recognition based on 2D Gabor filters", The Imaging Science Journal, Vol.62, No.3, pp.127-138, 2014.

C.B. Hsu, J.C. Lee, S.J. Chuang, et al., "Gaussian directional pattern for dorsal hand vein recognition", The Imaging Science Journal, Vol.63, No.1, pp.54-62, 2014.

J.C. Lee, T.M. Lo and C.P. Chang, et al., "Dorsal hand vein recognition based on directional filter bank", Signal, Image and Video Processing, Vol.10, No.1, pp.145-152, 2016.

J.W. Sun and W. Abdulla, "Palm vein recognition by combining Curvelet transform and Gabor filter", Biometric Recognition 8th Chinese Conference, Jinan, China, Vol.8232, pp.314-321, 2013.

P.O. Ladoux, C. Rosenberger and B. Dorizzi, "Palm vein verification system based on SIFT matching", Advances in Biometrics Proceeding third International Conference, Berlin, Germany, pp.1290-1298, 2009.

X. Jia, D.Y. Xue, J.J. Cui, et al., "Dorsal hand vein recognition algorithm based on Ridgelet transformation of divided blocks", Pattern Recognition and Artificial Intelligence, Vol.24, No.3, pp.346-352, 2011. (in Chinese)

X. Jia, D.Y. Xue, J.J. Cui, et al., "Vein recognition based on fusing multi HMMs with Contourlet subband energy observations", Journal of Electronics and Information Technology, Vol.33, No.8, pp.1877-1882, 2011. (in Chinese)

X. Jia, J.J. Cui, D.Y. Xue, et al., "Identity recognition based on multi feature sparse representation of dorsal hand vein image", Chinese Journal of Scientific Instrument, Vol.32, No.10, pp.2267-2274, 2011. (in Chinese)

L.Y. Wang, G. Leedham and D.S. Cho, "Minutiae feature analysis for infrared hand vein pattern biometrics", Pattern Recognition, Vol.41, No.3, pp.920-929, 2008.

A. Kumar and K.V. Prathyusha, "Personal authentication using hand vein triangulation and knuckle shape", IEEE Transactions on Image Processing, Vol.9, No.18, pp.2127-2136, 2009.

Y.P. Hu, Z.Y. Wang, X.P. Yang, et al., "Hand vein recognition based on the connection lines of reference point and feature point", Infrared Physics and Technology, Vol.62, pp.110-114, 2014.

Y.D. Wang and W.P. Liao, "Hand vein recognition based on feature coding", Proceedings of the 7th Chinese conference on Biometric Recognition, Guangzhou, China, pp.165-175, 2012.

P. Anika, H. Daniel and B. Christoph, "Feature extraction from vein images using spatial information and chain codes", Information Security Technical Report, Vol.17, No.1-2, pp.26-35, 2012.

K.S. Wu, J.C. Lee, T.M. Lo, et al., "A secure palm vein recognition system", Journal of Systems and Software, Vol.86, No.11, pp.2870-2876, 2013.

D.Y. Xue, X. Jia, J.J. Cui, et al., "Vein image feature extraction and matching based on regional shapes", Journal of Northeastern University, Vol.33, No.1, pp.35-38+64, 2012. (in Chinese)

X. Wang, T.X. Han and S. Yan, "An HOG-LBP human detector with partial occlusion handling", IEEE International Conference on Computer Vision, Kyoto, Japan, pp.32-39, 2010.

Z. Yang, F. Yao, K. Fan, et al., "Text dimensionality reduction with mutual information preserving mapping", Chinese Journal of Electronics, Vol.26, No.5, pp.35-41, 2017.

D.D. Lee and H.S. Seung, "Learning the parts of objects by non-negative matrix factorization", Nature, Vol.401, No.6755, pp.788-791, 1999.

W.Q. Yuan, R. Wang and S.H. Sun, "Palm-dorsa vein recognition based on two dimensional Fisher linear discriminant", Journal of Computer Applications, Vol.30, No.3, pp.646-649, 2010.

Y.L. Yin, L.L. Liu and X.W. Sun, "SDUMLA-HMT:A Multimodal Biometric Database", The 6th Chinese Conference on Biometric Recognition, Beijing, China, pp.260-268, 2011.

C. Wen, G. Zhou, J. Gao, et al., "Object recognition based on improved context model", Chinese Journal of Electronics, Vol.27, No.3, pp.573-581, 2018.

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