Comparison of wavelet, Gabor and curvelet transform for face recognition

• Autorzy: Zhang J. , Wang Y. , Zhang Z. , Xia C.
• Języki publikacji: EN

Abstrakty

EN

There has been much research about using Gabor wavelet for face recognition. Other multiscale geometrical tools, such as curvelet and contourlet, have also been used for face recognition, thus it is interesting to know which method performs best, especially under illumination and expression changes. In this paper, we make a systematic comparison of wavelet, Gabor and curvelet for recognition, and find the best subband irrelevant to expression and illumination changes. We combine the multiscale analysis with subspace decomposition as our algorithm. Experiments show that for expression changes, the properties of the coarse layer of curvelet and wavelet are very good. Whilst for illumination changes, the low frequency parts of the two methods are similarly influenced, but the detail coefficients of curvelet and the high frequency of wavelet work fine with PCA, with the former outperforming the latter. When these two factors change simultaneously, the detail layer of curvelet is better relative to the others.

Słowa kluczowe

EN

wavelet transform; Gabor wavelet; curvelet transform; face recognition; multiscale analysis

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Optica Applicata
• Rocznik: 2011
• Tom: Vol. 41, nr 1
• Strony: 183--193
• Opis fizyczny: Bibliogr. 17 poz.

Twórcy

autor

Zhang J.

autor

Wang Y.

autor

Zhang Z.

autor

Xia C.

• Computer Science and Engineering School, Xian University of Technology, Xi'an, 710048, P.R. China

Bibliografia

• [1] WISKOTT L., FELLOUS J.M., KUIGER N., VON DER MALSBURG C., Face recognition by elastic bunch graph matching, IEEE Transactions on Pattern Analysis and Machine Intelligence 19 (7), 1997,pp. 775–779.
• [2] DAI DAO-QING, YAN HONG, Wavelets and face recognition, [In] Face Recognition, I-Tech Education and Publishing, Vienna, Austria, 2007.
• [3] KEMAL EKENEL H., SANKUR B., Multiresolution face recognition, Image and Vision Computing 23(5),2005,pp. 469–477.
• [4] CANDÈS E.J., DONOHO D.L., Curvelets – A Surprisingly Effective Nonadaptive Representation for Objects with Edges, Vanderbilt University Press, Nashville, 2000, pp. 105–120.
• [5] CANDÈS E.J., DONOHO D.L., New tight frames of curvelets and optimal representations of objects with C2 singularities, Communications on Pure and Applied Mathematics 57 (2), 2004, pp. 219–266.
• [6] CANDÈS E.J., DEMANET L., DONOHO D.L., YING L., Fast discrete curvelet transforms, Multiscale Modeling and Simulation 5 (3), 2006, pp. 861–899.
• [7] ZHANG JIULONG, ZHANG ZHIYU, HUANG WEI et al., Face recognition based on curvefaces,International Conference on Natural Computing, 2007.
• [8] ZHANG JIU-LONG, LI PENG, Facial feature extraction by curvelet and LDA, Journal of Computational Information Systems 5 (3), 2008, pp. 1333–1339.
• [9] MAJUMDAR A., BHATTACHARYA A., Face recognition by multiresolution curvelet transform on bit quantized facial images, International Conference on Computational Intelligence and Multimedia Applications, 2007.
• [10] GABOR D., Theory of communications, Journal of the Institute of Electronics Engineers 93, 1946,pp. 429–457.
• [11] DAUGMAN J.G., Uncertainty relation for resolution in space, spatial-frequency, and orientation optimized by two-dimensional visual cortical filters, Journal of the Optical Society of America A 2 (7), 1985, pp. 1160–1169.
• [12] LINLIN SHEN, LI BAI, FAIRHURST M., Gabor wavelets and general discriminant analysis for face identification and verification, Image and Vision Computing 25 (5), 2007, pp. 553–563.
• [13] ZHONGLONG ZHENG, FAN YANG, WENAN TAN, JIONG JIA, JIE YANG, Gabor feature-based face recognition using supervised locality preserving projection, Signal Processing 87 (10), 2007,pp. 2473–2483
• [14] XUDONG XIE, KIN-MAN LAM, Gabor-based kernel PCA with doubly nonlinear mapping for face recognition with a single face image, IEEE Transactions on Image Processing 15 (9), 2006,pp. 2481–2492.
• [15] CHENGJUN LIU, Gabor-based kernel PCA with fractional power polynomial models for face recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence 26 (5), 2004,pp. 572–581.
• [16] CHENGJUN LIU, WECHSLER H., Gabor feature based classification using the enhanced Fisher linear discriminant model for face recognition, IEEE Transactions on Image Processing 11 (4), 2002,pp. 467–476.
• [17] WEN GAO, BO CAO, SHIGUANG SHAN, XILIN CHEN, DELONG ZHOU, XIAOHUA ZHANG, DEBIN ZHAO,The CAS-PEAL Large-Scale Chinese Face Database and baseline evaluations, IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans 38 (1), 2008, pp. 149–161.