Abstract
In this paper, a novel method for independent component analysis (ICA) with 2-D Principle Component Analysis (2DPCA) in face recognition is presented, called 2DPCA-ICA. In this method, 2DPCA is used for dimension reduction, and ICA for recognition. As opposed to the method for ICA based on PCA in face recognition (PCA-ICA), 2DPCA is based on 2-D face image matrix, an image covariance matrix is constructed directly using 2-D image matrix, and its eigenvectors corresponding to the several larger eigenvalues are derived for whitened image matrix. It overcomes the shortcomings of PCA-ICA. To test 2DPCA-ICA and evaluate its performance, experiments are performed on Yale and ORL (Olivetti Research Laboratory) face database. Correct recognition rate of 2DPCA-ICA across all trials is higher than that of PCA-ICA and 2DPCA. Experimental results also show that features of face image extracted are more efficient by way of 2DPCA-ICA. Therefore, 2DPCA-ICA is more valid in face recognition.
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References
Bartlett, M.S.: Face Image Analysis by Unsupervised Learning and Redundancy Reduction. PH.D Thesis of University of California, 27–37 (1998)
Yang, Q., Tang, X.O.: Recent Advances in Subspace Analysis for Face Recognition. In: Li, S.Z., Lai, J.-H., Tan, T., Feng, G.-C., Wang, Y. (eds.) SINOBIOMETRICS 2004. LNCS, vol. 3338, pp. 275–287. Springer, Heidelberg (2004)
Yang, J., Zhang, D.: Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 26(1), 131–137 (2004)
Comon, P.: Signal Processing. 36(3), 287–134 (1994)
Liu, C.: Enhanced Independent Component Analysis of Gabor Features for Face Recognition. IEEE Transactions on Neutral Networks 14, 919–928 (2003)
Havarinen, A., Oja, E.: Independent Component Analysis: Algorithm and Applications. Neural Networks 13(4-5), 411–430 (2000)
Yuen, P.C., Lai, J.H.: Face Representation Using Independent Component Analysis. Pattern Recognition 35, 1247–1257 (2002)
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Gan, Jy., Li, Cz., Zhou, Dp. (2007). A Novel Method for 2DPCA-ICA in Face Recognition. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Contemporary Intelligent Computing Techniques. ICIC 2007. Communications in Computer and Information Science, vol 2. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74282-1_135
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DOI: https://doi.org/10.1007/978-3-540-74282-1_135
Publisher Name: Springer, Berlin, Heidelberg
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