Neuro Fuzzy Network and Wavelet Gabor For Face Detection
DOI:
https://doi.org/10.31642/JoKMC/2018/010807Keywords:
Face detection, Gabor wavelet, Neurofuzzy Network.Abstract
This paper presents a face detection technique based on two techniques: wavelet Gabor filter for extract features from the localized facial image and neuro fuzzy system used as classifier depending on the features that extract , where it is used to determine the faces in the input image by draw boxes around the faces. The neurofuzzy network will be train on 128 image (69 face and 59 non face, size of each image 16*27 pixel in gray scale , this mean it trained to choose between two classes “face†and “non-face†images.
   Our approach has been tested on eight common images with different face number in image and different number of fuzzy set. We got the best detection rate is 89.3% in case threshold equal 0.2 and in case number of fuzzy set equal 2. The stages of this work are implemented in MATLAB 7.0 environment.
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B. Moghaddam and A. Pentland, “Probabilistic visual learning for object recognition,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no.7. pp. 696-710, July, 1997. DOI: https://doi.org/10.1109/34.598227
S. Horikawa, T. Furuhashi, and Y. Uchikawa, "On fuzzy modeling using fuzzy neural networks with the backpropagation algorithm", IEEE Trans. Neural Networks, vol. 3, pp. 801-806, 1992. DOI: https://doi.org/10.1109/72.159069
L.-X. Wang, "Adaptive Fuzzy systems and control Design and stability analysi"s, Prentice Hall, New Jersey, 1994. 4. J. S. Taur and C. W. Tao , " A New Neuro-Fuzzy Classifier with Application to On-Line Face Detection and Recognition", Journal of VLSI Signal Processing Systems , Volume 26 Issue 3, Nov. 2000 , Pages 397 - 409. 5. X. Zhu, D. Ramanan. "Face detection, pose estimation and landmark localization in the wild", Computer Vision and Pattern Recognition (CVPR) Providence, Rhode Island, June 2012.
Olivier J. Bernier, Jean-Emmanuel Viallet, and Michel Collobert, "A Fast and Accurate Face Detector Based on Neural Networks ", IEEE transaction pn pattern analysis and machine intelligence, Vol. 23, No. 1, 2001 DOI: https://doi.org/10.1109/34.899945
B. Kosko, "Neural Networks and Fuzzy Systems", Englewood Cliffs, NJ: Prentice-Hall, 1991.
Y. Hayashi and J. J. Buckley, “Approximations between fuzzy expert systems and neural networks”, Int. J. Approx. Reas., vol. 10, pp. 63–73, 1994. DOI: https://doi.org/10.1016/0888-613X(94)90009-4
J. S. R. Jang and C. T. Sun, “Functional equivalence between radial basis function networks and fuzzy inference systems", IEEE Trans. Neural Networks, vol. 4, pp. 156–159, 1993. DOI: https://doi.org/10.1109/72.182710
E. H. Mamdani and S. Assilian, “An experiment in linguistic synthesis with a fuzzylogic controller”. Int. J. Man-Mach. Stud., vol. 7, pp. 1–13, 1975. DOI: https://doi.org/10.1016/S0020-7373(75)80002-2
T. Takagi and M. Sugeno, “Fuzzy identification of systems and its application to modeling and contro", IEEE Trans. Syst., Man, Cybern., vol. SMC-15, pp. 116–132, 1985. DOI: https://doi.org/10.1109/TSMC.1985.6313399
H. Ishibuchi, M. Nii, and I. B. Turksen, “Bidirectional bridge between neural networks and linguistic knowledge: Linguistic rule extraction and learning from linguistic rules”, in Proc. IEEE Int. Conf. Fuzzy Syst. FUZZ-IEEE’98, Anchorage, AK, May 1998, pp. 1112–1117.
S. K. Pal and S. Mitra, "Neuro-fuzzy Pattern Recognition: Methods in Soft Computing", New York: Wiley, 1999.
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Copyright (c) 2014 Raidah Salim Mohammed
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