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International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.11, No.4, Apr. 2019

Discrete Complex Fuzzy Transform based Face Image Recognition Method

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Author(s)

Turker Tuncer, Sengul Dogan, Erhan Akbal

Index Terms

Face recognition;fuzzy transform;classification;local pattern

Abstract

In this paper, a novel discrete complex fuzzy transform (DCFT) and the proposed DCFT based facial image recognition method is presented. The presented DCFT consists of histogram extraction, peak points of histogram calculation and images construction. 3 real and 3 complex images are constructed using DCFT. Also, 3 angular images and 3 vector image are calculated using the real and complex images. To create real and complex images, polynomial and smith fuzzy sets are used in this paper. Briefly, 12 image are constructed using DCFT. In order to demonstrate effect of the proposed DCFT, face images data sets and local binary pattern (LBP) are used to create facial image recognition method. In this method, LBP is applied on the each DCFT image and 12 x 256 size of feature are extracted. Also, maximum pooling is applied on this feature set to obtain 256 size of feature. In the classification phase, support vector machine (SVM) and k nearest neighborhood (KNN) classifiers are used. The comparisons clearly demonstrate that the proposed DCFT is increased facial image recognition capability.

Cite This Paper

Turker Tuncer, Sengul Dogan, Erhan Akbal, " Discrete Complex Fuzzy Transform based Face Image Recognition Method", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.11, No.4, pp. 1-7, 2019.DOI: 10.5815/ijigsp.2019.04.01

Reference

[1]Turk, M.A. and Pentland, A.P., 'Face Recognition Using Eigenfaces', in, Computer Vision and Pattern Recognition, 1991. Proceedings CVPR'91., IEEE Computer Society Conference on, (IEEE, 1991)

[2]Yang, G. and Huang, T.S., 'Human Face Detection in a Complex Background', Pattern recognition, 1994, 27, (1), pp. 53-63.

[3]Zhang, W., Shan, S., Gao, W., Chen, X., and Zhang, H., 'Local Gabor Binary Pattern Histogram Sequence (Lgbphs): A Novel Non-Statistical Model for Face Representation and Recognition', in, Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on, (IEEE, 2005)

[4]Ahonen, T., Hadid, A., and Pietikainen, M., 'Face Description with Local Binary Patterns: Application to Face Recognition', IEEE Transactions on Pattern Analysis & Machine Intelligence, 2006, (12), pp. 2037-2041.

[5]Zhang, B., Gao, Y., Zhao, S., and Liu, J., 'Local Derivative Pattern Versus Local Binary Pattern: Face Recognition with High-Order Local Pattern Descriptor', IEEE transactions on image processing, 2010, 19, (2), pp. 533-544.

[6]Jain, A.K. and Li, S.Z., Handbook of Face Recognition, (Springer, 2011)

[7]Ahonen, T., Hadid, A., and Pietikäinen, M., 'Face Recognition with Local Binary Patterns', in, European conference on computer vision, (Springer, 2004)

[8]Suruliandi, A., Meena, K., and Rose, R.R., 'Local Binary Pattern and Its Derivatives for Face Recognition', IET computer vision, 2012, 6, (5), pp. 480-488.

[9]Xu, J., Cha, M., Heyman, J.L., Venugopalan, S., Abiantun, R., and Savvides, M., 'Robust Local Binary Pattern Feature Sets for Periocular Biometric Identification', in, Biometrics: Theory Applications and Systems (BTAS), 2010 Fourth IEEE International Conference on, (IEEE, 2010)

[10]Juefei-Xu, F. and Savvides, M., 'Subspace-Based Discrete Transform Encoded Local Binary Patterns Representations for Robust Periocular Matching on Nist’s Face Recognition Grand Challenge', IEEE transactions on image processing, 2014, 23, (8), pp. 3490-3505.

[11]Hassaballah, M. and Aly, S., 'Face Recognition: Challenges, Achievements and Future Directions', IET computer vision, 2015, 9, (4), pp. 614-626.

[12]Kim, T.-K. and Kittler, J., 'Locally Linear Discriminant Analysis for Multimodally Distributed Classes for Face Recognition with a Single Model Image', IEEE transactions on pattern analysis and machine intelligence, 2005, 27, (3), pp. 318-327.

[13]Woodward Jr, J.D., Horn, C., Gatune, J., and Thomas, A., Biometrics: A Look at Facial Recognition', (RAND CORP SANTA MONICA CA, 2003)

[14]Ojala, T., Pietikainen, M., and Maenpaa, T., 'Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns', IEEE transactions on pattern analysis and machine intelligence, 2002, 24, (7), pp. 971-987.

[15]Ojala, T., Pietikäinen, M., and Harwood, D., 'A Comparative Study of Texture Measures with Classification Based on Featured Distributions', Pattern recognition, 1996, 29, (1), pp. 51-59.

[16]Shan, C., Gong, S., and McOwan, P.W., 'Facial Expression Recognition Based on Local Binary Patterns: A Comprehensive Study', Image and vision Computing, 2009, 27, (6), pp. 803-816.

[17]Zhao, Y., Jia, W., Hu, R.-X., and Min, H., 'Completed Robust Local Binary Pattern for Texture Classification', Neurocomputing, 2013, 106, pp. 68-76.

[18]Song, K., Yan, Y., Zhao, Y., and Liu, C., 'Adjacent Evaluation of Local Binary Pattern for Texture Classification', Journal of Visual Communication and Image Representation, 2015, 33, pp. 323-339.

[19]Kaya, Y., Ertuğrul, Ö.F., and Tekin, R., 'Two Novel Local Binary Pattern Descriptors for Texture Analysis', Applied Soft Computing, 2015, 34, pp. 728-735.

[20]Mehta, R. and Egiazarian, K., 'Dominant Rotated Local Binary Patterns (Drlbp) for Texture Classification', Pattern Recognition Letters, 2016, 71, pp. 16-22.

[21]Chen, X., Zhou, Z., Zhang, J., Liu, Z., and Huang, Q., 'Local Convex-and-Concave Pattern: An Effective Texture Descriptor', Information Sciences, 2016, 363, pp. 120-139.

[22]Liu, L., Fieguth, P., Zhao, G., Pietikäinen, M., and Hu, D., 'Extended Local Binary Patterns for Face Recognition', Information Sciences, 2016, 358, pp. 56-72.

[23]Adnan, S.M., Irtaza, A., Aziz, S., Ullah, M.O., Javed, A., and Mahmood, M.T., 'Fall Detection through Acoustic Local Ternary Patterns', Applied Acoustics, 2018, 140, pp. 296-300.

[24]Liu, P., Guo, J.-M., Chamnongthai, K., and Prasetyo, H., 'Fusion of Color Histogram and Lbp-Based Features for Texture Image Retrieval and Classification', Information Sciences, 2017, 390, pp. 95-111.

[25]Wang, Y., Shi, C., Wang, C., and Xiao, B., 'Ground-Based Cloud Classification by Learning Stable Local Binary Patterns', Atmospheric Research, 2018, 207, pp. 74-89.

[26]Yuan, F., Xia, X., and Shi, J., 'Mixed Co-Occurrence of Local Binary Patterns and Hamming-Distance-Based Local Binary Patterns', Information Sciences, 2018, 460, pp. 202-222.

[27]Singh, C., Walia, E., and Kaur, K.P., 'Color Texture Description with Novel Local Binary Patterns for Effective Image Retrieval', Pattern recognition, 2018, 76, pp. 50-68.

[28]Yang, C.-S. and Yang, Y.-H., 'Improved Local Binary Pattern for Real Scene Optical Character Recognition', Pattern Recognition Letters, 2017, 100, pp. 14-21.

[29]Citraro, L., Mahmoodi, S., Darekar, A., and Vollmer, B., 'Extended Three-Dimensional Rotation Invariant Local Binary Patterns', Image and vision Computing, 2017, 62, pp. 8-18.

[30]Hurney, P., Waldron, P., Morgan, F., Jones, E., and Glavin, M., 'Night-Time Pedestrian Classification with Histograms of Oriented Gradients-Local Binary Patterns Vectors', IET intelligent transport systems, 2014, 9, (1), pp. 75-85.

[31]Samaria, F.S. and Harter, A.C., 'Parameterisation of a Stochastic Model for Human Face Identification', in, Applications of Computer Vision, 1994., Proceedings of the Second IEEE Workshop on, (IEEE, 1994)

[32]Weeks, A.R., Fundamentals of Electronic Image Processing, (SPIE Optical Engineering Press Bellingham, 1996)

[33]Libor Spacek's Facial Image Database, F.D.h.c.e.a.u.m.a.f.h.a.J., 2018).

[34]Phillips, P.J., Wechsler, H., Huang, J., and Rauss, P.J., 'The Feret Database and Evaluation Procedure for Face-Recognition Algorithms', Image and vision Computing, 1998, 16, (5), pp. 295-306.

[35]Milborrow, S., Morkel, J., and Nicolls, F., 'The Muct Landmarked Face Database', Pattern Recognition Association of South Africa, 2010, 201, (0).

[36]Martinez, A. M. (1998). The AR face database. CVC Technical Report24.

[37]Taheri, S., and Toygar, Ö. 'Animal classification using facial images with score-level fusion. IET Computer Vision, 2018, 12 (5), pp. 679-685.