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Personal ID Image Normalization Using ISO/IEC 19794-5 Standards for Facial Recognition Improvement

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Mathematical Modelling and Scientific Computation (ICMMSC 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 283))

Abstract

Facial recognition methods are the basis for security systems. Identification and verification are the Facial recognition methods are used to identify and authorize persons. For automated face recognition, the facial images should be normalized to improve the efficiency of recognition. In this paper we normalize personal ID images using ISO/IEC 19794-5 standards. Experimental results show that the proposed algorithm significantly improved face recognition efficiency.

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References

  1. Somasundaram, K., Palaniappan, N.: Adaptive Low Bit Rate Facial Feature Enhanced Residual Image Coding Method using SPIHT for Compressing Personal ID Images. Int. J. Electron. Commun. 65, 589–594 (2011)

    Article  Google Scholar 

  2. Wang, P., Tran, L.C., Ji, Q.: Improving Face Recognition by Online Image Alignment. In: 18th IEEE International Conference on Pattern Recognition, pp. 311–314. IEEE Press, New York (2006)

    Google Scholar 

  3. Biometric Data Interchange Formats – Part 5: Face Image Data Draft Revision 19794–5 (2004)

    Google Scholar 

  4. Yang, M.-H., Kriegman, D.J., Ahuja, N.: Detecting Faces in Images: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 24, 34–58 (2002)

    Article  Google Scholar 

  5. Chai, D., Ngan, K.N.: Locating Facial Region of a Head-and-shoulders Color Image. In: IEEE International Conference on Automatic Face and Gesture Recognition, pp. 124–129. IEEE Press, New York (1998)

    Chapter  Google Scholar 

  6. Hsu, R.L., Mottaleb, M.A., Jain, A.K.: Face Detection in Color Images. IEEE Trans. Pattern Anal. Mach. Intell. 24, 696–706 (2002)

    Article  Google Scholar 

  7. Chan, Y.H., Abu-Baker, S.A.R.: Face Detection System Based on Feature-Based Chrominance Color Information. In: IEEE International Conference on Computer Graphics, pp. 153–158. IEEE Press, New York (2004)

    Google Scholar 

  8. Frakas, L.G., Munro, I.R.: Anthropometric Facial Proportion in Medicine. Charles C. Thomas Publisher, Springfield IL (1987)

    Google Scholar 

  9. Wang, Q., Yang, J.: Eye Detection in Facial Images with Unconstrained Background. J. Pattern Recognition Research 1, 55–62 (2006)

    Article  Google Scholar 

  10. Viola, P., Jones, M.: Rapid Object Detection using a Boosted Cascade of Simple Features. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 511–518. IEEE Press, New York (2001)

    Google Scholar 

  11. Tang, X., Ou, Z., Su, T., Sun, H., Zhao, P.: Robust Precise Eye Location by AdaBoost and SVM Techniques. In: International Symposium on Neural Networks, pp. 93–98 (2005)

    Google Scholar 

  12. Friedman, J., Hastie, T., Tibshirani, R.: Additive Logistic Regression: a Statistical View of Boosting, Technical Report, Stanford University (1998)

    Google Scholar 

  13. Bonney, B., Ives, R., Etter, D., Du, Y.: Iris Pattern Extraction using Bit Planes and Standard Deviations. In: Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, vol. 1, pp. 582–586. IEEE Press, New York (2004)

    Google Scholar 

  14. Computer Vision Laboratory, Faculty of Computer and Information Science, University of Ljubljana, Slovenia, http://lrv.fri.uni-lj.si/facedb.html

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© 2012 Springer-Verlag Berlin Heidelberg

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Somasundaram, K., Palaniappan, N. (2012). Personal ID Image Normalization Using ISO/IEC 19794-5 Standards for Facial Recognition Improvement. In: Balasubramaniam, P., Uthayakumar, R. (eds) Mathematical Modelling and Scientific Computation. ICMMSC 2012. Communications in Computer and Information Science, vol 283. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28926-2_47

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  • DOI: https://doi.org/10.1007/978-3-642-28926-2_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28925-5

  • Online ISBN: 978-3-642-28926-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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