Advances in Biometric Person Authentication: International by Matti Pietikäinen, Abdenour Hadid (auth.), Stan Z. Li,

By Matti Pietikäinen, Abdenour Hadid (auth.), Stan Z. Li, Zhenan Sun, Tieniu Tan, Sharath Pankanti, Gérard Chollet, David Zhang (eds.)

This ebook constitutes the refereed lawsuits of the overseas Workshop on Biometric popularity platforms, IWBRS 2005, held in Beijing, China in October 2005 in the scope of ICCV 2005, the foreign convention on computing device imaginative and prescient. This workshop combines the once a year chinese language convention on Biometric popularity (Sinobiometrics 2005).

The 32 revised complete papers have been rigorously reviewed and chosen from one hundred thirty submissions. The papers handle the issues of automated and trustworthy authentication of people in face, iris, fingerprint, palmprint, speaker, writing and different biometrics, and give a contribution new principles to analyze and improvement of trustworthy and useful ideas for biometric authentication.

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Additional resources for Advances in Biometric Person Authentication: International Wokshop on Biometric Recognition Systems, IWBRS 2005, Beijing, China, October 22-23, 2005. Proceedings

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2002. 6. F. Perronnin, J. L. Dugelay: Robust Score Normalization for Relational Approaches to Face Authentication, 12th European Signal Processing Conference, Sep. 2004. 7. J. Phillips, P. Grother, R. J. Micheals, D. M. Blackburn, E. Tabassi, J. M. Bone: Face Recognition Vendor Test 2002 Evaluation Report, NISTIR 6965, Mar. 2003. 8. J. Phillips, H. Moon, P. J. Rauss, and S. Rizvi: The FERET Evaluation Methodology for Face Recognition Algorithms, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.

When compared to these more reasonable model, the linear degeneration model used in the AT algorithm is rather simple. Especially when the illumination becomes much worse, the AT algorithm does not work well on illumination correction. As for ICR algorithm, as we conclude above, it does work well when dealt with the side-lamp-house. However, usually it does not single out to apply for illumination correction for face images. Compared with most face illumination normalization methods, the AT and ICR method do have their advantages.

On Automatic Face and Gesture Recognition (2004) 457–463 13. : Rapid object detection using a boosted cascade of simple features. In: IEEE Proc. Int. Conf. on Computer Vision and Pattern Recognition. Volume 1. (2001) 511–518 14. : Support vector machines for 3d object recognition. IEEE Trans. com Abstract. The problem of illumination makes the face recognition still an unsolved problem. A new normalization method was presented which is illumination invariant in face recognition. The histogram equalization was applied to improve the performances of the AT (Affine Transform) algorithm.

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