Abstract
As patterns in a palmprint have abundance of invariance, the inter-class and intra-class variability of these features makes it difficult for just one set of features to capture this variability. This inspires us to propose a hybrid feature extraction and fusion approach for palmprint recognition based on texture information available in the palm. Scale, shift and rotation (Affine) invariance, good directional sensitivity properties of Dual-tree Complex Wavelets makes it a choice to capture texture features at global level. Local Binary Pattern on the other hand being gray-scale and rotation invariant, captures local fine textures effectively. These local features are sensitive to position and orientation of the palm image. Canonical Correlation Analysis is used to combine the features at the descriptor level which ensures that the information captured from both the features are maximally correlated and eliminate the redundant information giving a more compact representation. Experimental results demonstrate an accuracy of 97.2% at an EER of 3.2% on CASIA palmprint database.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Zhang, D., Kong, W.K., You, J., Wong, M.: Online palmprint identification. IEEE Trans. Pattern Anal. Mach. Intell. 25(9), 1041–1050 (2003)
Kong, A.W.-K., Zhang, D.: Feature-Level Fusion for Effective Palmprint Authentication. In: Zhang, D., Jain, A.K. (eds.) ICBA 2004. LNCS, vol. 3072, pp. 761–767. Springer, Heidelberg (2004)
Zuo, W., Lin, Z., Guo, Z., Zhang, D.: The multiscale competitive code via sparse representation for palmprint verification. In: Proc. of CVPR, pp. 2265–2272 (2010)
You, et al: On hierarchical palmprint coding with multiple features for personal identification in large databases. IEEE Trans. Circuits Syst. Video Tech. (2004)
Kong, W., Zhang, D., Li, W.: Palmprint feature extraction using 2-d gabor filters. Pattern Recog. 36(10), 2339–2347 (2003)
Pan, et al.: Palmprint recognition using fusion of local and global features. In: Proc. of the Int. Symposium on Intelligent Signal Processing and Communication Systems, pp. 642–645 (2007)
Jain, A., Feng, J.: Latent palmprint matching. IEEE Trans. Pattern Anal. Mach. Intell. 31(5), 1032–1047 (2009)
Kumar, A., Zhang, D.: Personal authentication using multiple palmprint representation. Pattern Recognition 38, 1695–1704 (2005)
Wu, X., Zhang, D., And Wang, K.: Palm line extraction and matching for personal authentication. IEEE Trans. Syst. Man Cybern. Part A 36(5), 978–987 (2006b)
Liu, L., Zhang, D., You, J.: Detecting wide lines using isotropic nonlinear filtering. IEEE Trans. Image Process. 16(6), 1584–1595 (2007)
Han, C.-C.: A hand-based personal authentication using a coarse-to-fine strategy. Image and Vision Computing 22, 909–918 (2004)
CASIA Palmprint database, http://www.idealtest.org/dbDetailForUser.do?id=5
Chen, G.Y., Xie, W.F.: Pattern recognition with SVM and dual-tree complex. Image and Vision Computing 25(6), 960–966 (2007)
Wang, et al: Palmprint identification using boosting local binary pattern. In: Proceedings of ICPR, pp. 503–506 (2006)
Ojala, et al: Multiresolution gray-scale and rotation invariant texture classification with Local Binary Patterns. IEEE Transactions on PAMI 24(7), 971–987 (2002)
Selesnick, et al.: The dual-tree complex wavelet transform. IEEE Signal Processing Magazine 22(2), 123–151 (2005)
Sun, Q.-S., et al.: A theorem on the generalized canonical projective vectors. Pattern Recognition 38, 449–452 (2005)
Kong, A., Zhang, D., Kamel, M.: Palmprint identification using feature-level fusion. Pattern Recog. 39(3), 478–487 (2006a)
Kong, A., Zhang, D.: Competitive coding scheme for palmprint verification. In: Proceedings of the 17th International Conference on Pattern Recognition, pp. 520–523 (2004)
UST Hand Image database, http://www4.comp.polyu.edu.hk/~csajaykr/Database/palm/2dhand.html
Zhang, et al.: A Comparative Study of Palmprint Recognition Algorithms. ACM Computing Surveys 44(1) (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Manasa, N.L., Govardhan, A., Satyanarayana, C. (2013). Hybrid Approach for Palmprint Recognition Using Compound Features. In: Prasath, R., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. Lecture Notes in Computer Science(), vol 8284. Springer, Cham. https://doi.org/10.1007/978-3-319-03844-5_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-03844-5_3
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03843-8
Online ISBN: 978-3-319-03844-5
eBook Packages: Computer ScienceComputer Science (R0)