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Face Recognition with a Sobel Edge Detector and the Choquet Integral as Integration Method in a Modular Neural Networks

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Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization

Part of the book series: Studies in Computational Intelligence ((SCI,volume 601))

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Abstract

In this paper a method for response integration of Modular Neural Networks, based on Choquet Integral applied to face recognition is presented. Type-1 and Type-2 fuzzy systems for edge detections based on the Sobel, which is a pre-processing applied to the training data for better performance in the modular neural network. The Choquet integral is an aggregation operator that in this case is used as a method to integrate the outputs of the modules of the modular neural networks (MNN).

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References

  1. Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8(2), 679–698 (1986)

    Article  Google Scholar 

  2. Choquet, G.: Theory of capacities. Ann. Inst. Fourier, Grenoble 5, 131–295 (1953). doi:10.5802/aif.53

    Article  MathSciNet  Google Scholar 

  3. Hidalgo, D.: Fuzzy inference systems type 1 and type 2 as integration methods in neural networks for multimodal biometrics and Me-optimization by means of genetic algorithms. Master Thesis, Tijuana Institute of Technology (2008)

    Google Scholar 

  4. Horiuchi, T., Kato, S.: A study on Japanese historical character recognition using modular neural networks. In: IEEE Fourth International Conference on Innovative Computing, Information and Control, pp. 1507–1510 (2009)

    Google Scholar 

  5. Kirsch, R.: Computer determination of the constituent structure of biological images. Comput. Biomed. Res. 4, 315–328 (1971)

    Article  Google Scholar 

  6. Kwak, K.C., Pedrycz, W.: Face recognition: a study in information fusion using fuzzy integral. Pattern Recogn. Lett. 26, 719–733 (2005)

    Article  Google Scholar 

  7. Liu, H.C., Wu D.B., Jheng Y.D., Chen, C.C., Chien, M.F., Sheu, T.W.: Choquet integral with respect to sigma-fuzzy measure. In: International Conference on Mechatronics and Automation, Changchun, China 978-1-4244-2693-5/09. IEEE (2009)

    Google Scholar 

  8. Martínez, G.E., Melin, P., Olivia, M.D., Castillo, O.: Face recognition with Choquet integral in modular neural networks. In: Recent Advances on Hybrid Approaches for Designing Intelligent Systems. Springer International Publishing, Switzerland (2014). doi:10.1007/978-3-319-05170-3_30

  9. Meena, Y.K., Arya, K.V., Kala, R.: Classification using redundant mapping in modular neural networks. In: Second World Congress on Nature and Biologically Inspired Computing, Kitakyushu, Fukuoka, Japan, 15–17 Dec 2010

    Google Scholar 

  10. Melin, P., Gonzalez, C., Bravo, D., Gonzalez, F., Martínez, G.: Modular neural networks and fuzzy Sugeno integral for pattern recognition: the case of human face and fingerprint. In: Hybrid Intelligent Systems: Design and Analysis. Springer, Heidelberg (2007)

    Google Scholar 

  11. Melin, P., Mendoza, O., Castillo O.: Face recognition with an improved interval type-2 fuzzy logic Sugeno integral and modular neural networks. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 41(5) (2011)

    Google Scholar 

  12. Mendoza, O., Melin, P., Castillo, O., Castro, J.: Comparison of fuzzy edge detectors based on the image recognition rate as performance index calculated with neural networks. In: Soft Computing for Recognition Based on Biometrics. Studies in Computational Intelligence, vol. 312, pp. 389–399 (2010)

    Google Scholar 

  13. Mendoza, O., Melin, P.: Quantitative evaluation of fuzzy edge detectors applied to neural networks or image recognition. In: Advances in Research and Developments in Digital Systems, pp. 324–335 (2011)

    Google Scholar 

  14. Murofushi, T., Sugeno, M.: Fuzzy measures and fuzzy integrals. Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama, Japan (2000)

    Google Scholar 

  15. Prewitt, J.M.S.: Object enhancement and extraction. In: Lipkin, B.S., Rosenfeld, A. (eds.) Picture Analysis and Psychopictorics, pp. 75–149. Academic Press, New York (1970)

    Google Scholar 

  16. Sánchez, D., Melin, P.: Modular neural network with fuzzy integration and its optimization using genetic algorithms for human recognition based on iris, ear and voice biometrics. In: Soft Computing for Recognition Based on Biometrics, pp. 85–102 (2010)

    Google Scholar 

  17. Sánchez, D., Melin, P., Castillo, O., Valdez, F.: Modular neural networks optimization with hierarchical genetic algorithms with fuzzy response integration for pattern recognition. MICAI, pp. 247–258 (2012)

    Google Scholar 

  18. Song, J., Li, J.: Lebesgue theorems in non-additive measure theory. Fuzzy Sets Syst. 149(3), 543–548 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  19. Sobel, I.: Camera models and perception. Ph.D. Thesis, Stanford University, Stanford, CA (1970)

    Google Scholar 

  20. Sugeno, M.: Theory of fuzzy integrals and its applications. Thesis Doctoral, Tokyo Institute of Technology, Tokyo, Japan (1974)

    Google Scholar 

  21. Timonin, M.: Robust optimization of the Choquet integral. Fuzzy Sets Syst. 213, 27–46 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  22. Wang, Z., Klir, G.: Generalized measure Theory. Springer, New York (2009)

    Book  MATH  Google Scholar 

  23. Wanga, P., Xua, L., Zhou, S.M., Fan, Z., Li, Y., Feng, S.: A novel Bayesian learning method for information aggregation in modular neural networks. In: Expert Systems with Applications, vol. 37, pp. 1071–1074. Elsevier, New York (2010)

    Google Scholar 

  24. Yanga, W., Chen, Z.: New aggregation operators based on the Choquet integral and 2-tuple linguistic information. Expert Syst. Appl. 39, 2662–2668 (2012)

    Article  Google Scholar 

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Acknowledgment

We thank the MyDCI program of the Division of Graduate Studies and Research, UABC, Tijuana Institute of Technology, and the financial support provided by our sponsor CONACYT contract grant number: 189350.

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Authors and Affiliations

  1. University of Baja California, Tijuana, Mexico

    Gabriela E. Martínez & Olivia D. Mendoza

  2. Tijuana Institute of Technology, Tijuana, Mexico

    Patricia Melin & Oscar Castillo

Authors
  1. Gabriela E. Martínez
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  2. Patricia Melin
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  3. Olivia D. Mendoza
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  4. Oscar Castillo
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Corresponding author

Correspondence to Patricia Melin .

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Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Patricia Melin

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

  3. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    Janusz Kacprzyk

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Martínez, G.E., Melin, P., Mendoza, O.D., Castillo, O. (2015). Face Recognition with a Sobel Edge Detector and the Choquet Integral as Integration Method in a Modular Neural Networks. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization. Studies in Computational Intelligence, vol 601. Springer, Cham. https://doi.org/10.1007/978-3-319-17747-2_5

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  • DOI: https://doi.org/10.1007/978-3-319-17747-2_5

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  • Online ISBN: 978-3-319-17747-2

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