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Avatar Facial Biometric Authentication Using Wavelet Local Binary Patterns

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Security and Privacy Preserving in Social Networks

Part of the book series: Lecture Notes in Social Networks ((LNSN))

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Abstract

Virtual worlds (e.g., Second Life) are populated by different types of people, businesses, and organizations. Users of virtual worlds, either individuals or organizations, might abuse the flexibility and adaptability offered by virtual environment by engaging in criminal activities. Even terrorist organizations have been active in virtual worlds. These organizations recently have used the virtual worlds for recruitment and to train their new members in an environment that is very similar to the real one. Since avatars are not just virtual creations as they have a great social and psychological correspondence with their creators, applying biometric techniques on avatars can give the law enforcement agencies and security experts the ability to identify who the actual users behind these avatars are. There is a mounting pressure to have techniques for verifying the real identities of the inhabitants of virtual worlds to secure cyberworld from incessant criminal activities (e.g., verbal harassment, fraud, money laundering, data or identity theft). In order to reduce the gap between our ability to recognizing human faces and avatar faces and to develop reliable tools for protecting virtual environments, we will discuss in this chapter how we can use different versions of local binary pattern (LBP) operators (traditional LBP, multi-scale LBP and hierarchical multi-scale LBP) to recognize avatar faces from two different virtual worlds (Second Life and Entropia Universe). This chapter includes a definition of discrete wavelet transform from a face recognition research perspective, a summary of previous work done on this topic, characteristics of the datasets used in the experiments as well as some suggestions for future work.

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References

  1. Gavrilova, M.L., Yampolskiy, R.V.: Applying biometric principles to avatar recognition. In: Proceedings of the International Conference on Cyberworlds, pp. 179–186, 2010

    Google Scholar 

  2. Ajina, S., Yampolskiy, R.V., Amara, N.E.B.: Avatar facial biometric authentication. In: 2nd International Conference on Image Processing Theory, Tools and Applications, Paris, pp. 2–5, 2010

    Google Scholar 

  3. Second Life. Available from: www.secondlife.com

  4. Active Worlds. Available from: www.activeworlds.com

  5. Entropia Universe. Available from: www.entropiauniverse.com

  6. Yampolskiy, R.V., Klare, B., Jain, A.K.: Face recognition in the virtual world: recognizing avatar faces. In: Proceedings of the 11th IEEE International Conference on Machine Learning and Applications, Boca Raton, FL, pp. 40--45 (2012)

    Google Scholar 

  7. O’Brien, N.: Spies watch rise of virtual terrorists. Available from: http://www.news.com.au/top-stories/spies-watch-rise-of-virtual-terrorists/story-e6frfkp9-1111114075761

  8. Yampolskiy, R.V., Govindaraju, V.: Behavioral biometrics for verification and recognition of malicious software agents. In: Sensors and Command Control Communications and Intelligence (C31) Technologies for Homeland Security and Homeland Defense VII. SPIE Defense and Security Symposium, Orlando, 2008

    Google Scholar 

  9. Ajina, S., Yampolskiy, R.V., Amara, N.E.B.: Evaluation of SVM classification of avatar facial recognition. In: Proceedings of the 8th International Conference on Advances in Neural Networks, pp. 132–142, 2011

    Google Scholar 

  10. Mohamed, A.A., Yampolskiy, R.V.: An improved LBP algorithm for avatar face recognition. In: 23th International Symposium on Information, Communication and Automation Technologies, Sarajevo, pp. 1–5, 2011

    Google Scholar 

  11. Garcia, C., Zikos, G., Tziritas, G.: A wavelet-based framework for face recognition. In: Proceedings of the 5th European Conference on Computer Vision, Freiburg, Allemagne, pp. 84–92, 1998

    Google Scholar 

  12. Harmon, L.: The recognition of faces. Sci. Am. 229(5), 71–82 (1973)

    Article  Google Scholar 

  13. Mazloom, M., Ayat, S.: Combinational method for face recognition: wavelet, PCA and ANN. In: International Conference on Digital Image Computing: Techniques and Applications, Canberra, pp. 90–95, 2008

    Google Scholar 

  14. Wang, H., Yang, S., Liao, W.: An improved PCA face recognition algorithm based on the discrete wavelet transform and the support vector machines. In: International Conference on Computational Intelligence and Security Workshops, Harbin, pp. 308–311, 2007

    Google Scholar 

  15. Luo, B., Zhang, Y., Pan, Y.-H.: Face recognition based on wavelet transform and SVM. In: IEEE International Conference on Information Acquisition, Hong Kong and Macau, pp. 373–377, 2005

    Google Scholar 

  16. Ojala, T., Pietikäinen, M., Harwood, D.: A comparative study of texture measures with classification based on feature distributions. Pattern Recognit. 29(1), 51–59 (1996)

    Article  Google Scholar 

  17. Meng, J., Gao, Y., Wang, X., Lin, T., Zhang, J.: Face recognition based on local binary patterns with threshold. In: IEEE International Conference on Granular Computing, San Jose, pp. 352–356, 2010

    Google Scholar 

  18. Wang, W., Chang, F., Zhao, J., Chen, Z.: Automatic facial expression recognition using local binary pattern. In: 8th World Congress on Intelligent Control and Automation, Jinan, pp. 6375–6378, 2010

    Google Scholar 

  19. Ahonen, T., Hadid, A., Pietikäinen, M.: Face description with local binary patterns: application to face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 28(12), 2037–2041 (2006)

    Article  Google Scholar 

  20. Tan, N., Huang, L., Liu, C.: Face recognition based on a single image and local binary pattern. In: 2nd International Symposium on Intelligent Information Technology Application, Shanghai, pp. 366–370, 2008

    Google Scholar 

  21. Liu, X., Du, M., Jin, L.: Face features extraction based on multi-scale LBP. In: 2nd International Conference on Signal Processing Systems, Dalian, pp. v2 438–v2 441, 2010

    Google Scholar 

  22. Liao, S., Zhu, X., Lei, Z., Zhang, L., Li, S.: Learning multi-scale local binary patterns for face recognition. In: International Conference on Biometrics. Lecture Notes in Computer Science, vol. 4642, pp. 828–837. Springer, Berlin (2007)

    Google Scholar 

  23. Mäenpää, T., Pietikäinen, M.: Multi-scale binary patterns for texture analysis. In: Proceedings of the 13th Scandinavian Conference on Image Analysis, pp. 885–892, 2003

    Google Scholar 

  24. Turtinen, M., Pietikäinen, M.: Contextual analysis of textured scene images. In: Proceedings of the British Machine Vision Conference, pp. 849–858, 2006

    Google Scholar 

  25. Chan, C., Kittler, J., Messer, K.: Multi-scale binary pattern histogram for face recognition. In: International Conference on Biometrics. Lecture Notes in Computer Science, vol. 4642, pp. 809–818. Springer, Berlin (2007)

    Google Scholar 

  26. Guo, Z., Zhang, L., Zhang, D., Xuanqin, M.: Hierarchical multi-scale LBP for face and palmprint recognition. In: Proceedings of the IEEE International Conference on Image Processing, Hong Kong, pp. 4521–4524 (2010)

    Google Scholar 

  27. Mohamed, A.A., D’Souza, D., Baili, N., Yampolskiy, R.V.: Avatar face recognition using wavelet transform and hierarchical multi-scale LBP. In: Proceedings of the 10th IEEE International Conference on Machine Learning and Applications, Honolulu, pp. 194–199, 2011

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Engineering and Computer Science, University of Louisville, Louisville, KY, USA

    Abdallah A. Mohamed & Roman V. Yampolskiy

Authors
  1. Abdallah A. Mohamed
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  2. Roman V. Yampolskiy
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Correspondence to Abdallah A. Mohamed .

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Editors and Affiliations

  1. LIUPPA Laboratory, University of Pau and Adour Countries, Anglet, France

    Richard Chbeir

  2. Ticket Laboratory, Antonine University, Baabda, Lebanon

    Bechara Al Bouna

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Mohamed, A.A., Yampolskiy, R.V. (2013). Avatar Facial Biometric Authentication Using Wavelet Local Binary Patterns. In: Chbeir, R., Al Bouna, B. (eds) Security and Privacy Preserving in Social Networks. Lecture Notes in Social Networks. Springer, Vienna. https://doi.org/10.1007/978-3-7091-0894-9_10

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  • DOI: https://doi.org/10.1007/978-3-7091-0894-9_10

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  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-7091-0893-2

  • Online ISBN: 978-3-7091-0894-9

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