Abstract
Although palmprint based authentication approaches have shown promising results recently, efforts are still required to achieve higher performance with low time complexity for their use in real-life high security applications. Based on these requirements, the concept of two level matching scheme using line matching in Hough space and Curve segment Hausdorff Distance (CsHD) are explored and developed for speedy and accurate palmprint identification in this paper. This method combines the advantages of both local and global feature approaches, which is able to not only absorb the variance of palmprints by transforming the palmprint pattern into a new domain, but also overcome the problem of high computation complexity when the database size increases. The system employs low-resolution palmprint images captured by normal digital camera and achieves higher identification accuracy with lower time complexity.
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References
Riha, Z., Matyas, V.: Biometric authentication systems. FI MU Report Series, FIMU-RS-2000-08 (November 2000)
Zhang, L., Zhang, D.: Characterication of palmprint by wavelet signatures via directional context modeling. IEEE Transactions on Systems, Man. And Cybernetics-Part B: Cybernetics 34(3), 1335–1347 (2004)
Zhou, Y.X., Leung, M.K.H.: Shape Recognition using Curve Segment Hausdorff Distance. In: Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006) (2006)
Zhang, D., Kong, W.K., You, J., Wong, M.: Online palmprint identification. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(9), 1041–1050 (2003)
Cheng, F.H., Hsu, W.H., Chen, M.Y.: Recognition of handwritten Chinese characters by modified Hough Transform techniques. IEEE Transactions on Pattern Analysis and Machine Intelligence 11(4), 901–916 (1989)
Li, Z.N.: Stereo correspondence based on line matching in Hough space using Dynamic Programming. IEEE Transactions on System. Man. and Cybernetics 24(1), 144–152 (1994)
Huttenlocher, D.P., Klandeman, G.A., Rucklidge, W.J.: Comparing images using the Hausdorff distance. IEEE Transactions on Pattern Analysis and Machine Intelligence 15(9), 850–863 (1993)
Gao, Y.S., Leung, M.K.H.: Face recognition using line edge map. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(6), 764–779 (2002)
Manjunath, B.S.: Introduction to MPE-7:multimedia content description interface. Wiley, Chichester (2002)
Yi, X.L., Camps, O.I.: Line-Based recognition using a multidimentional Hausdorff Distance. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(9), 901–916 (1999)
Chen, J.Y., Leung, M.K.H., Gao, Y.S.: Noisy logo recognition using line segment Hausdorff Distance. Pattern Recognition 36, 943–955 (2003)
Palmprint database from Biometric Research Center, The Hong Kong Polytechnic University. Available: http://www4.comp.polyu.edu.hk/~biometrics/
Duta, N., Jain, A.K.: Matching of palmprints. Pattern Recognition Letters 23, 477–485 (2002)
You, J., Zhang, W.-K., Kong., Z.D., Cheung, K.H.: On hierarchical palmprint coding with multiple features for personal identification in large databases. IEEE Transactions on Circuits and Systems for Video Technology 14(2), 234–243 (2004)
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© 2006 Springer-Verlag Berlin Heidelberg
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Li, F., Leung, M.K.H., Yu, X. (2006). A Two-Level Matching Scheme for Speedy and Accurate Palmprint Identification. In: Cham, TJ., Cai, J., Dorai, C., Rajan, D., Chua, TS., Chia, LT. (eds) Advances in Multimedia Modeling. MMM 2007. Lecture Notes in Computer Science, vol 4352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69429-8_33
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DOI: https://doi.org/10.1007/978-3-540-69429-8_33
Publisher Name: Springer, Berlin, Heidelberg
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