Abstract
In this paper we describe a number of experiments relating to PCA-based palmprint and face recognition. The experiments were designed to determine the influence of different training sets used for the construction of the eigenpalm and eigenface spaces on the recognition efficiency of biometric systems. The results of the recognition experiments, obtained using three palmprint databases (PolyU, FER1, FER2) and one face database (XM2VTSDB), suggest that it is possible to design a biometric recognition system that is robust enough to successfully recognize palmprints (or faces) even in cases when the eigenspaces are constructed from completely independent sets of palmprints or face images. Furthermore, the experiments show that for PCA-based face-recogni-tion systems with an eigenspace that is constructed by using palmprint-image databases, and PCA-based palmprint-recognition systems with an eigenspace that is constructed using a face-image database, the recognition rates are unexpectedly improved compared to the classic approach.
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References
Zhang, D.D.: Palmprint Authentication. Kluwer Academic Publishers, Boston (2004)
Maltoni, D., et al.: Handbook of Fingerprint Recognition. Springer, New York (2003)
Li, S.Z., Jain, A.K.: Handbook of Face Recognition. Springer, New York (2005)
Kumar, A., Zhang, D.: Integrating palmprint and face for user authentication. In: Proc. Multi Modal User Authentication Workshop, Santa Barbara, pp. 107–112 (2003)
Jolliffe, I.T.: Principal Component Analysis. Springer, New York (1986)
Lu, G., Zhang, D., Wang, K.: Palmprint recognition using eigenpalms. Pattern Recognition Letters 24, 1463–1467 (2003)
Connie, T., Teoh, A., Goh, M., Ngo, D.: Palmprint Recognition with PCA and ICA. In: Conference of Image and Vision Computing New Zealand 2003, pp. 227–232 (2003)
Ribarić, S., Fratrić, I.: A Biometric Identification System Based on Eigenpalm and Eigenfinger Features. IEEE Trans. Patt. Anal. Mach. Intell. 27, 1698–1709 (2005)
Turk, M., Pentland, A.: Eigenfaces for Recognition. J. of Cognitive Neuroscience 3, 71–86 (1991)
Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection. IEEE Trans. Patt. Anal. Mach. Intell. 19, 711–720 (1997)
Moghaddam, B.: Principal manifolds and bayesian subspaces for visual recognition. IEEE Trans. Patt. Anal. Mach. Intell Intelligence 24, 780–788 (2002)
XM2VTSDB Face Database, http://www.ee.surrey.ac.uk/CVSSP/xm2vtsdb
PolyU Palmprint Database, http://www.comp.polyu.edu.hk/~biometrics/
Ozawa, S., Pang, S., Kasabov, N.: A Modified Incremental Principal Component Analysis for On-line Learning of Feature Space and Classifier. In: 8th Pacific Rim Internatinal Conference on Artificial Intelligence, Auckland, pp. 231–240 (2004)
Hall, P., Martin, R.: Incremental Eigenanalysis for Classification. In: Proc. British Machine Vision Conference, pp. 286–295 (1998)
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Krevatin, I., Ribarić, S. (2008). Some Unusual Experiments with PCA-Based Palmprint and Face Recognition. In: Schouten, B., Juul, N.C., Drygajlo, A., Tistarelli, M. (eds) Biometrics and Identity Management. BioID 2008. Lecture Notes in Computer Science, vol 5372. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89991-4_13
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DOI: https://doi.org/10.1007/978-3-540-89991-4_13
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