Abstract
This paper presents a new approach to face recognition which uses a new local descriptor, called Weber Local Descriptor (WLD).To extract local information further, the idea of dividing faces into small regions was adopted. Feature histogram is extracted from every region and concatenated into a single feature vector to efficiently represent the face image. The recognition is performed using a nearest neighbor classifier in the computed feature space with Chi square as a dissimilarity measure. The experiments on ORL, FERET, Yale face database show that the proposed approach is not only better than holistic methods such as PCA, KPCA, 2DPCA but also superior to LBP. Meanwhile, it’s robust to pose, noise, facial expressions and lightings.
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References
O’Toole, A.J., Phillips, P.J., An, X., Dunlop, J.: Demographic effects on estimates of automatic face recognition performance. In: Automatic Face & Gesture Recognition Workshops, vol. 30(3), pp. 169–176 (2011)
Bozorgtabar, B., Noorian, F., Rezai Rad, G.A.: Comparison of different PCA based Face Recognition algorithms using Genetic Programming. In: International Symposium on Telecommunications, pp. 801–805 (2010)
Wang, Y., Zhang, Y.: The facial expression recognition based on KPCA. In: International Conference on Intelligent Control and Information Processing, pp. 365–368 (2010)
Ying, L., Liang, Y.: A human face recognition method by improved Modular 2DPCA. In: IEEE International Symposium on IT in Medicine and Education, pp. 7–11 (2011)
Diamantaras, K.I., Kung, S.Y.: Principal Component Neural Networks: Theory and Applications. Wiley, NewYork (1996)
Scholkopf, B., Smola, A., Muller, K.R.: Nonlinear component analysis as a Kernel eigenvalue problem. Neural Computing 10, 1299–1319 (1998)
Li, J., Allinson, N.M.: A comprehensive review of current local features for computer vision. Neurocomputing 71, 1771–1787 (2008)
Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1615–1630 (2005)
David, G.: Lowe, Distinctive image features from scale invariant keypoints. Int. J. Computer Vis. 60(2), 91–110 (2004)
Dalal, N., Triggs, B.: Histograms of oriented gradients of human detection. In: CVPR (2005)
Ojala, T., Pietikäinen, M., Mäenpää, T.: Multiresolution gray scale and rotation invariant texture analysis with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 971–987 (2002)
Li, W., Pang, Y., Yuan, Y., Pan, J.: Fully affine invariant SURF for image matching. Neurocomputing 85, 6–10 (2012)
Chen, J., Shan, S., et al.: WLD: A robust local image descriptor. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(9), 1705–1720 (2010)
Ahilapriyadharshini, R., Arivazhagan, S., Gowthami, M.: Weber Local Descriptor based object recognition. In: IEEE International Conference on Advanced Communication Control and Computing Technologies, pp. 115–119 (2012)
Ahonen, T., Hadid, A., Pietikäinen, M.: Face recognition with local binary patterns. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3021, pp. 469–481. Springer, Heidelberg (2004)
DelMarco, S.P., Tom, V., Webb, H.F.: A Theory of Automatic Parameter Selection for Feature Extraction With Application to Feature-Based Multisensor Image Registration. IEEE Trans. on Image Processing 16(11), 2733–2742 (2007)
Phillips, P.J., Moon, H., Rizvi, S.A., Rauss, P.J.: The FERET evaluation methodol-ogy for face-recognition algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 22(10), 1090–1104 (2000)
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Rui, T., Yang, Z., Liu, F., Jiang, S., Li, H. (2013). Block-Based Face Recognition Using WLD. In: Huet, B., Ngo, CW., Tang, J., Zhou, ZH., Hauptmann, A.G., Yan, S. (eds) Advances in Multimedia Information Processing – PCM 2013. PCM 2013. Lecture Notes in Computer Science, vol 8294. Springer, Cham. https://doi.org/10.1007/978-3-319-03731-8_76
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DOI: https://doi.org/10.1007/978-3-319-03731-8_76
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03730-1
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