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An Application of Graphic Tools and Analytic Hierarchy Process to the Description of Biometric Features

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Artificial Intelligence and Soft Computing (ICAISC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10842))

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Abstract

AHP is a well-known method supporting decision-making based on a pairwise comparison process. Previous results of our research show that this tool can be effectively used to describe biometric features, in particular facial parts. In this paper, we present an original and innovative development of this approach augmented by a graphical interface that allows the user to get rid of restrictions in the form of certain numerical (linguistic) values, which were adapted beforehand, answering questions about comparisons of individual features. The presented results of experiments show the efficiency and ease of use of AHP based on a graphical interface in a context of description of biometric features. An application a proper non-linear transformation which parameters can be found on a basis of Particle Swarm Optimization can significantly improve the consistency of expert’s evaluation.

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References

  1. Alonso, J.A., Lamata, M.T.: Consistency in the analytic hierarchy process: a new approach. Int. J. Uncertain. Fuzz. 14, 445–459 (2006)

    Article  Google Scholar 

  2. Bertillon, A.: La photographie judiciaire: avec un appendice sur la classification et l’identification anthropométriques. Gauthier-Villars, Paris (1890)

    Google Scholar 

  3. Bertillon, A.: Identification anthropométrique: instructions signaltiques. Imprimerie administrative, Melun (1983)

    Google Scholar 

  4. Dolecki, M., Karczmarek, P., Kiersztyn, A., Pedrycz, W.: Face recognition by humans performed on basis of linguistic descriptors and neural networks. In: Proceedings of the 2016 International Joint Conference on Neural Networks (IJCNN 2016), pp. 5135–5140 (2016)

    Google Scholar 

  5. Frowd, C.D., Hancock, P.J.B., Carson, D.: EvoFIT: a holistic, evolutionary facial imaging technique for creating composites. ACM Trans. Appl. Percept. 1, 19–39 (2004)

    Article  Google Scholar 

  6. Fukushima, S., Ralescu, A.L.: Improved retrieval in a fuzzy database from adjusted user input. J. Intell. Inf. Syst. 5, 249–274 (1995)

    Article  Google Scholar 

  7. Grycuk, R., Gabryel, M., Korytkowski, M., Scherer, R.: Content-based image indexing by data clustering and inverse document frequency. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds.) BDAS 2014. CCIS, vol. 424, pp. 374–383. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-06932-6_36

    Chapter  Google Scholar 

  8. Grycuk, R., Gabryel, M., Korytkowski, M., Scherer, R., Voloshynovskiy, S.: From single image to list of objects based on edge and blob detection. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2014. LNCS (LNAI), vol. 8468, pp. 605–615. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07176-3_53

    Chapter  Google Scholar 

  9. Grycuk, R., Gabryel, M., Nowicki, R., Scherer, R.: Content-based image retrieval optimization by differential evolution. In: 2016 IEEE Congress on Evolutionary Computation (CEC), pp. 86–93 (2016)

    Google Scholar 

  10. Kacprzyk, J., Pedrycz, W.: Springer Handbook of Computational Intelligence. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-43505-2

    Book  MATH  Google Scholar 

  11. Karczmarek, P., Kiersztyn, A., Pedrycz, W., Dolecki, M.: Linguistic descriptors and analytic hierarchy process in face recognition realized by humans. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2016. LNCS (LNAI), vol. 9692, pp. 584–596. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39378-0_50

    Chapter  Google Scholar 

  12. Karczmarek, P., Kiersztyn, A., Pedrycz, W., Rutka, P.: A study in facial features saliency in face recognition: an analytic hierarchy process approach. Soft. Comput. 21, 7503–7517 (2017)

    Article  Google Scholar 

  13. Karczmarek, P., Kiersztyn, A., Rutka, P., Pedrycz, W.: Linguistic descriptors in face recognition: a literature survey and the perspectives of future development. In: SPA 2015 Signal Processing, Algorithms, Architectures, Arrangements, and Applications, Conference Proceedings, pp. 98–103 (2015)

    Google Scholar 

  14. Karczmarek, P., Pedrycz, W., Kiersztyn, A.: Graphic interface to analytic hierarchy process and its optimization. IEEE Trans. Fuzzy Syst. (submitted)

    Google Scholar 

  15. Kasiński, A., Florek, A., Schmidt, A.: The PUT face database. Image Process. Commun. 13, 59–64 (2008)

    Google Scholar 

  16. Kennedy, J.F., Eberhart, R.C., Shi, Y.: Swarm Intelligence. Academic Press, San Diego (2001)

    Google Scholar 

  17. Kiersztyn, A., Karczmarek, P., Dolecki, M., Pedrycz, W.: Linguistic descriptors and fuzzy sets in face recognition realized by humans. In: Proceedings of the 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016), pp. 1120–1126 (2016)

    Google Scholar 

  18. Kiersztyn, A., Karczmarek, P., Rutka, P., Pedrycz, W.: Quantitative methods for linguistic descriptors in face recognition. In: Zapała, A. (ed.) Recent Developments in Mathematics and Informatics, Contemporary Mathematics and Computer Science, vol. 1, pp. 123–138. The John Paul II Catholic University of Lublin Press, Lublin (2016)

    Google Scholar 

  19. Kumar, N., Berg, A.C., Belhumeur, P.N., Nayar, S.K.: Attribute and simile classifiers for face verification. In: Proceedings of IEEE 12th International Conference on Computer Vision, pp. 365–372 (2009)

    Google Scholar 

  20. Kumar, N., Berg, A.C., Belhumeur, P.N., Nayar, S.K.: Describable visual attributes for face verification and image search. IEEE Trans. Pattern Anal. Mach. Intell. 33, 1962–1977 (2011)

    Article  Google Scholar 

  21. Kurach, D., Rutkowska, D., Rakus-Andersson, E.: Face classification based on linguistic description of facial features. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2014. LNCS (LNAI), vol. 8468, pp. 155–166. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07176-3_14

    Chapter  Google Scholar 

  22. van Laarhoven, P.J.M., Pedrycz, W.: A fuzzy extension of Saaty’s priority theory. Fuzzy Sets Syst. 11, 199–227 (1983)

    Article  MathSciNet  Google Scholar 

  23. Laughery, K.R., Fowler, R.H.: Sketch artists and Identi-kit, procedure for recalling faces. J. Appl. Psychol. 65, 307–316 (1980)

    Article  Google Scholar 

  24. Matthews, M.L.: Discrimination of Identikit constructions of faces: evidence for a dual processing strategy. Percept. Psychophys. 23, 153–161 (1978)

    Article  Google Scholar 

  25. Moreira, J.L., Braun A., Musse, S.R.: Eyes and eyebrows detection for performance driven animation. In: 2010 23rd SIBGRAPI Conference on Graphics, Patterns and Images, pp. 17–24 (2010)

    Google Scholar 

  26. Nakayama, M., Miyajima, K., Iwamoto, H., Norita, T.: Interactive human face retrieval system based on linguistic expression. In: Proceedings of 2nd International Conference on Fuzzy Logic and Neural Networks, IIZUKA 1992, vol. 2, pp. 683–686 (1992)

    Google Scholar 

  27. Nakayama, M., Norita, T., Ralescu, A.: A fuzzy logic based qualitative modeling of image data. In: Proceedings of lPMU 1992, pp. 615–618 (1992)

    Google Scholar 

  28. Norita, T.: Fuzzy theory in an image understanding retrieval system. In: Ralescu, A.L. (ed.) Applied Research in Fuzzy Technology. International Series in Intelligent Technologies, vol. 1, pp. 215–251. Springer Science+Business Media, New York (1994). https://doi.org/10.1007/978-1-4615-2770-1_6

    Chapter  Google Scholar 

  29. Rahman, A., Sufyan Beg, M.M.: Face sketch recognition using sketching with words. Int. J. Mach. Learn. Cyber. 6, 597–605 (2015)

    Article  Google Scholar 

  30. Saaty, T.L.: Fundamentals of Decision Making and Priority Theory with the Analytic Hierarchy Process. Analytic Hierarchy Process Series, vol. 6. RWS Publications, Pittsburgh (2000)

    Google Scholar 

  31. Saaty, T.L.: The Analytic Hierarchy Process. McGraw-Hill, New York (1980)

    MATH  Google Scholar 

  32. Saaty, T.L., Mariano, R.S.: Rationing energy to industries: priorities and input-output dependence. Energy Syst. Policy 3, 85–111 (1979)

    Google Scholar 

  33. Saaty, T.L., Vargas, L.G.: Models, Methods, Concepts & Applications of the Analytic Hierarchy Process. Springer, New York (2012). https://doi.org/10.1007/978-1-4614-3597-6

    Book  MATH  Google Scholar 

  34. Sadr, J., Jarudi, I., Sinha, P.: The role of eyebrows in face recognition. Perception 32, 285–293 (2003)

    Article  Google Scholar 

  35. Sun, Y., Wang, X., Tang, X.: Deep learning face representation from predicting 10,000 classes. In: 2014 IEEE CVPR, pp. 1891–1898 (2014)

    Google Scholar 

  36. Wright, J., Yang, A.Y., Ganesh, A., Sastry, S.S., Ma, Y.: Robust face recognition via sparse representation. IEEE Trans. Pattern Anal. Mach. Intell. 31, 210–227 (2009)

    Article  Google Scholar 

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Acknowledgements

The authors are supported by National Science Centre, Poland (grant no. 2014/13/D/ST6/03244). Support from the Canada Research Chair (CRC) program and Natural Sciences and Engineering Research Council is gratefully acknowledged (W. Pedrycz).

Author information

Authors and Affiliations

  1. Institute of Mathematics and Computer Science, The John Paul II Catholic University of Lublin, ul. Konstantynów 1H, 20-708, Lublin, Poland

    Paweł Karczmarek & Adam Kiersztyn

  2. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, T6R 2V4, Canada

    Witold Pedrycz

  3. Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Witold Pedrycz

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

    Witold Pedrycz

Authors
  1. Paweł Karczmarek
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  2. Adam Kiersztyn
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  3. Witold Pedrycz
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Corresponding author

Correspondence to Paweł Karczmarek .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Karczmarek, P., Kiersztyn, A., Pedrycz, W. (2018). An Application of Graphic Tools and Analytic Hierarchy Process to the Description of Biometric Features. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2018. Lecture Notes in Computer Science(), vol 10842. Springer, Cham. https://doi.org/10.1007/978-3-319-91262-2_13

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  • DOI: https://doi.org/10.1007/978-3-319-91262-2_13

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