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Personal identity verification method based on lips photographs

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper presents a personal identification method based on lips photographs. This method uses a new approach to the extraction and classification of characteristic features of the mouth from photographs. It eliminates the drawbacks that occur during the acquisition of lip print images with the use of the forensic method that requires special tools. Geometrical dimensions of the entire mouth as well as of the upper and lower lips were adopted as the features, on the basis of which the verification is performed. An ensemble classifier was used for the classification of the features obtained. The effectiveness of the classifier has been verified experimentally.
Rocznik
Tom
Strony
59--65
Opis fizyczny
Bibliogr. 13 poz., rys., tab.
Twórcy
autor
  • Institute of Computer Science, University of Silesia, ul. Bedzinska 39, 41-200 Sosnowiec, Poland
autor
  • Institute of Computer Science, University of Silesia, ul. Bedzinska 39, 41-200 Sosnowiec, Poland
autor
  • Institute of Computer Science, University of Silesia, ul. Bedzinska 39, 41-200 Sosnowiec, Poland
autor
  • Faculty of Electronics and Information Technology, Warsaw University of Technology, ul. Nowowiejska 15, 00-665 Warsaw, Poland
autor
  • Faculty of Electronics and Information Technology, Warsaw University of Technology, ul. Nowowiejska 15, 00-665 Warsaw, Poland
Bibliografia
  • [1] BOLLE R., CONNELL J., PANKANTI S., RATHA N., SENIOR A. Guide to biometrics. 2004. Springer.
  • [2] CAO X., WEI Y., WEN F., SUN J. Face alignment by explicit shape regression. International Journal of Computer Vision, 2014, Vol. 107. pp. 177–90.
  • [3] CHORAS M. The lip as a biometric. Pattern Analysis and Applications, 2010, Vol. 13. pp. 105–112.
  • [4] DALAL N., TRIGGS B. Histograms of oriented gradients for human detection. IEEE Int. Conference of Computer Vision and Pattern Recognition (CVPR), 2005. pp. 886–893.
  • [5] GROSS R., MATTHEWS I., COHN J., KANADE T., BAKER S. Multi–pie. 8th IEEE international conference on Automatic Face & Gesture Recognition, 2008. pp. 1–8.
  • [6] JAIN A. K., FLYNN P., ROSS A. A. Handbook of biometrics. 2007. Springer, New York.
  • [7] LIENHART R., MAYDT J. An extended set of haar–like features for rapid object detection. Proceedings of International Conference on Image Processing, 2002, Vol. 1. pp. 900–903.
  • [8] NEWTON M. The encyclopedia of crime scene investigation. 2008. Checkmark Books.
  • [9] SAGONAS C., TZIMIROPOULOS G., ZAFEIRIOU S., PANTIC M. A semi–automatic methodology for facial landmark annotation. IEEE Int. Conference of Computer Vision and Pattern Recognition (Workshops) (CVPRW), 2013. pp. 896– 903.
  • [10] SHAOQING R., XUDONG C., YICHEN W., JIAN S. Face alignment at 3000 fps via regressing local binary features. IEEE Int. Conference of Computer Vision and Pattern Recognition (CVPR), 2014. pp. 1685–92.
  • [11] SIEGEL J., SAUKKO P., KNUPFER G. Encyclopedia of forensic science. 2013. Academic Press.
  • [12] WROBEL K., DOROZ R., PALYS M. A method of lip print recognition based on sections comparison. IEEE Int. Conference on Biometrics and Kansei Engineering (ICBAKE), 2013. pp. 47–52.
  • [13] XUEHAN X., DE LA TORRE F. Supervised descent method and its applications to face alignment. IEEE Int. Conference of Computer Vision and Pattern Recognition (CVPR), 2013. pp. 532–9.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7971ba99-e010-4479-8f71-d4b54963a66d
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