Abstract
Recently, handprint-based personal identification is widely being researched. Existing identification systems are nearly based on peg or peg-free stretched gray handprint images and most of them only using single feature to implement identification. In contrast to existing systems, color handprint images with incorporate gesture based on peg-free are captured and both hand shape features and palmprint texture features are used to facilitate coarse-to-fine dynamic identification. The wavelet zero-crossing method is first used to extract hand shape features to guide the fast selection of a small set of similar candidates from the database. Then, a modified LoG filter which is robust against brightness is proposed to extract the texture of palmprint. Finally, both global and local texture features of the ROI are extracted for determining the final output from the selected set of similar candidates. Experimental results show the superiority and effectiveness of the proposed approach.
This work is supported by science foundation for young teachers of Northeast Normal University, No. 20061002, China.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Wu, X., Wang, K., Zhang, F., Zhang, D.: Fusion of Phase And Orientation Information for Palmprint Authentication. IEEE, Los Alamitos
Wu, X., Zhang, D., Wang, K., Huang, B.: Palmprint classification using principal lines. Patt. Recog. 37, 1987–1998 (2004)
Wu, X., Wang, K.: A Novel Approach of Palm-line Extraction. In: Proceedings of International Conference on Image Processing (2004)
Duta, N., Jain, A.K., Mardia, K.V.: Matching of palmprint. Pattern Recognition letters 23, 477–485 (2002)
Zhang, D., Kong, W.K., You, J., Wong, M.: On-line palmprint identification. IEEE Trans. Patt. Anal. Mach. Intell. 25, 1041–1050 (2003)
Kong, W.K., Zhang, D., Li, W.: Palmprint feature extraction using 2-D Gabor filters. Patt. Recog. 36, 2339–2347 (2003)
Ribaric, S., Fratric, I.: A Biometric identification System Based on Eigenpalm and Eigenfinger Features. IEEE Transactions on Pattern Analysis and Machine Intelligence 27, 1698–1709 (2005)
Wu, X., Zhang, D., Wang, K.: Fisherpalms based palmprint recognition. Pattern Recognition Letters 24, 2829–2838 (2003)
Li, W., Zhang, D., Xu, Z.: Palmprint identification feature extraction Fourier Transform. International Journal of Pattern Recognition and Artificial Intelligence 16(4), 417–432 (2003)
Li, W., You, J., Zhang, D.: Texture-Based Palmprint Retrieval Using a Layered Search Scheme for Personal Identification. IEEE Transactions on Multmedia 7, 891–898 (2005)
You, J., Li, W., Zhang, D.: Hierarchical palmprint identification via multiple feature extraction. Pattern Recognition 35, 847–859 (2003)
Kan, C., Srinath, M.D.: Invariant character recognition with Zernike and orthogonal Fourier-Mellin moments. Pattern Recognition 35, 143–154 (2002)
Sanchez-Avila, C., Sanchez-Reillo, R.: Two different approaches for iris recognition using Gabor filters and multiscale zero-crossing representation. Pattern Recognition 38, 231–240 (2005)
Chang, C.-C., Tsai, P., Lin, C.-C.: SVD-based digital image watermarking scheme. Pattern Recognition Letters 26, 1577–1586 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kong, J., Qi, M., Lu, Y., Liu, X., Zhou, Y. (2006). A Fast and Robust Personal Identification Approach Using Handprint. In: Gunsel, B., Jain, A.K., Tekalp, A.M., Sankur, B. (eds) Multimedia Content Representation, Classification and Security. MRCS 2006. Lecture Notes in Computer Science, vol 4105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11848035_25
Download citation
DOI: https://doi.org/10.1007/11848035_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-39392-4
Online ISBN: 978-3-540-39393-1
eBook Packages: Computer ScienceComputer Science (R0)