Abstract
In this work a novel method for human face recognition that is based on fuzzy neural network has been presented. Here, Gabor wavelet transformation is used for extraction of features from face images as it deals with images in spatial as well as in frequency domain to capture different local orientations and scales efficiently. In face recognition problem multilayer perceptron (MLP) has already been adopted owing to its efficiency, but it does not capture overlapping and nonlinear manifolds of faces which exhibit different variations in illumination, expression, pose, etc. A fuzzy MLP on the other hand performs better than an MLP because fuzzy MLP can identify decision surfaces in case of nonlinear overlapping classes, whereas an MLP is restricted to crisp boundaries only. In the present work, a new approach for fuzzification of the feature sets obtained through Gabor wavelet transforms has been discussed. The feature vectors thus obtained are classified using a newly designed fuzzified MLP. The system has been tested on a composite database (DB-C) consisting of the ORL face database and another face database created for this purpose and a recognition rate of 97.875% with fuzzy MLP against a recognition rate of only 81.25% with MLP whose feature vectors were also obtained through same Gabor wavelet transforms has been obtained.
Similar content being viewed by others
References
Atick JJ, Griffin PA, Redlich NA (1995) Face recognition from live video. Adv Imaging 10(5):58–62
Bartlett MS, Movellan JR, Sejnowski TJ (2002) Face recognition by independent component analysis. IEEE Trans Neural Netw 13(6):1450–1464. doi:10.1109/TNN.2002.804287
Bevilacqua V, Cariello L, Carro G, Daleno D, Mastronardi G (2008) A face recognition system based on Pseudo 2D HMM applied to neural network coefficients. Soft Comput J 12:615–621
Bhattacharjee D, Basu DK, Nasipuri M, Kundu M (2002) Integration of kernel and DCT coefficient fuzzy matching for human face recognition. Found Comput Decis Sci J Pol 27(2):61–76
Bhattacharjee D, Basu DK, Nasipuri M, Kundu M (2004) Application of Gabor wavelet transformation for human face recognition. In: Proceedings of international conference on communications, devices and intelligent systems, CODIS, 8–10 January, Kolkata, India, pp 528–531
Bhuiyan A, Liu CH (2007) On face recognition using Gabor filters. In: Proceedings of world academy of science, engineering and technology, vol 22, pp 51–56
Cevikalp H, Neamtu M, Wilkes M, Barkana A (2005) Discriminative common vectors for face recognition. IEEE Trans PAMI 27(1):1–9
Chen W, Yuen PC, Huang J, Lai J (2005) A novel fisher criterion based St-subspace linear discriminant method for face recognition. In: Hao et al. Y (eds) CIS 2005, Part I, LNAI 3801, pp 933–940, Springer, Berlin
Er MJ, Shiqian W, Juwei L, Hock LT (2002) Face recognition with radial basis function neural networks. IEEE Trans Neural Netw 13(3):697–709. doi:10.1109/TNN.2002.1000134
Er MJ, Chen W, Wu S (2005) High-speed face recognition based on discrete cosine transform and RBF neural networks. IEEE Trans Neural Netw 16(3):679–691. doi:10.1109/TNN.2005.844909
Gottumukkal R, Asari VK (2004) An improved face recognition technique based on modular PCA approach. Pattern Recognit Lett 25:429–436. doi:10.1016/j.patrec.2003.11.005
Huang L, Zhang Z (2007) Face recognition using multiscale Gabor wavelet. In: Proceedings of IEEE PACRIM’07, pp 280–283
Intrator N, Reisfeld D, Yeshurun Y (1996) Face recognition using a hybrid supervised/unsupervised neural network. Pattern Recognit Lett 17:67–76. doi:10.1016/0167-8655(95)00089-5
Jain AK, Duin RPW, Mao J (2000) Statistical pattern recognition: a review. IEEE Trans PAMI 22(1):4–37
Keller JM, Hunt DJ (1985) Incorporating fuzzy membership functions into the perceptron algorithm. IEEE Trans Pattern Anal Mach Intell 7(6):693–699
Kim T, Kittler J (2005) Locally linear discriminant analysis for multimodally distributed classes for face recognition with a single model image. IEEE Trans PAMI 27(3):318–327
Klir GJ, Yuan B (1995) Fuzzy sets and fuzzy logic: theory and applications. PHI publication, New Delhi
Kohonen T (1989) Self-organization and associative memory. Springer, Berlin
Kung SY, Taur JS (1995) Decision-based neural networks with signal/image classification applications. IEEE Trans Neural Netw 6(1):170–181. doi:10.1109/72.363439
Kwok T, Yeung Y (1997) Objective functions for training new hidden units in constructive neural network. IEEE Trans Neural Netw 8(5):630–645. doi:10.1109/72.572102
Lam K, Yan H (1998) An analytic-to-holistic approach for face recognition based on a single frontal view. IEEE Trans PAMI 20:673–686
Lawrence S, Giles CL, Tsoi AC, Back AD (1997) Face recognition: a convolutional neural-network approach. IEEE Trans Neural Netw 8(1):98–113. doi:10.1109/72.554195
Li SZ, Lu J (1999) Face recognition using the nearest feature line method. IEEE Trans Neural Netw 10(2):439–443. doi:10.1109/72.750575
Lin S, Kung S, Lin L (1997) Face recognition/detection by probabilistic decision-based neural network. IEEE Trans Neural Netw 8(1):114–132. doi:10.1109/72.554196
Liu C (2004) Gabor-based kernel PCA with fractional power polynomial models for face recognition. IEEE Trans PAMI 26(5):572–581
Liu C, Wechsler H (2003) Independent component analysis of Gabor features for face recognition. IEEE Trans Neural Netw 14(4):919–928. doi:10.1109/TNN.2003.813829
Lyons M, Budynek JJ, Akamatsu S (1999) Automatic classification of single facial images. IEEE Trans PAMI 21(12):1357–1362
Manjunath BS, Ma WY (1996) Texture features for browsing and retrieval of image data. IEEE Trans PAMI 18(8):837–842
Marchand M, Golea M, Rujan P (1990) A convergence theorem for sequential learning in two-layer perceptrons. Europhys Lett 11:487–492. doi:10.1209/0295-5075/11/6/001
Ming Z, Fulcher J (1996) Face recognition using artificial neural network group-based adaptive tolerance (GAT) trees. IEEE Trans Neural Netw 7(3):555–567. doi:10.1109/72.501715
Moghaddam B, Nastar C, Pentland A (1996) A Bayesian similarity measure for direct image matching. Massachusetts Institute of Technology, Cambridge, MIT Media Lab PCS TR393
Neubauer C (1998) Evaluation of convolutional neural networks for visual recognition. IEEE Trans Neural Netw 9(1):685–696. doi:10.1109/72.701181
Oh B (2005) Face recognition using radial basis function network based on LDA. In: Proceedings of World Academy of Science, Engineering and Technology, vol 7, ISSN 1307-6884
Pandya AS, Macy RB (1996) Pattern recognition with neural networks in C ++. IEEE/CRC Press, Boca Raton
Phillips J, Moon H, Rizvi S, Rauss P (1999) The FERET evaluation methodology for face-recognition algorithms. NIST technical report NISTIR 6264
Samaria FS, Harter AC (1994) Parameterization of a stochastic model for human face identification. In: Proceedings of 2nd IEEE workshop on appn of comp. Vision Sarasota, FL
Scholkopf B, Smola A (2002) Learning with kernels: support vector machines, Regularization, Optimization and Beyond. MIT Press, Cambridge
Toygar O, Acan A (2004) Boosting face recognition speed with a novel divide-and conquer approach. In: Aykanat C et al. (eds) ISCIS 2004, LNCS, vol 3280. Springer, Berlin, pp 430–439
Turk M, Pentland A (1991) Eigenfaces for recognition. J Cogn Neurosci 3:71–86. doi:10.1162/jocn.1991.3.1.71
Virginia E (2000) Biometric identification system using a radial basis network. In: Proceedings 34th annual IEEE international Carnhan conference security technology, pp 47–51
Wiskott L et al (1997) Face recognition by elastic bunch graph matching. IEEE Trans Pattern Anal Mach Intell 19(7):775–779. doi:10.1109/34.598235
Zhang B, Guo Y (2001) Face recognition by wavelet domain associative memory. In: Proceedings of Int. symp. intell. multimedia, video, speech processing, pp 481–485
Zhang J, Yan Y, Lades M (1997) Face recognition: eigenface, elastic matching, and neural nets. Proc IEEE 85(9):1423–1435. doi:10.1109/5.628712
Zhang B, Zhang H, Ge SS (2004) Face recognition by applying Wavelet Subband representation and Kernel Associative Memory. IEEE Trans Neural Netw 15(1):166–177. doi:10.1109/TNN.2003.820673
Zhao T, Liang Z, Zhang D, Liu Y (2005) A novel null space-based kernel discriminant analysis for face recognition. In: Lee S-W, Li SZ (eds) ICB 2007, LNCS 4642, Springer, Berlin, pp 547–556
Acknowledgments
Authors are thankful to the “Centre for Microprocessor Application for Training Education and Research” and “Project on Storage Retrieval and Understanding of Video for Multimedia”, at the Department of Computer Science and Engineering, Jadavpur University, Kolkata, 700 032 for providing the necessary facilities for carrying out this work. First and second authors acknowledge with thanks the receipts of Jadavpur University Research Grant and AICTE Emeritus Fellowship (1-51/RID/EF(13)/2007-08), respectively.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Bhattacharjee, D., Basu, D.K., Nasipuri, M. et al. Human face recognition using fuzzy multilayer perceptron. Soft Comput 14, 559–570 (2010). https://doi.org/10.1007/s00500-009-0426-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00500-009-0426-0