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Tytuł artykułu

Acces control system using face image

Autorzy
Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Ensuring safety requires the use of access control systems. Traditional systems typically use proximity cards. Modern systems use biometrics to identify the user. Using biological characteristics for identification ensures a high degree of safety. In addition, biological characteristics cannot be neither lost nor stolen. This paper presents proposals for the access control system Rusing face image. The system operates in real time using camera image.
Rocznik
Strony
691--703
Opis fizyczny
Bibliogr. 18 poz., il.
Twórcy
autor
  • Czestochowa University of Technology Institute of Computer and Information Science Dabrowskiego 73, 42-200 Czestochowa, Poland, januszb@icis.pcz.pl
Bibliografia
  • AHLVERS U., ZÖLZER U., RAJAGOPALAN R. (2005) Model-free Face Detection and Head Tracking with Morphological Hole Mapping. EUSIPCO’05, Antalya, Turkey.
  • BAE H. and KIM S. (2005) Real-time face detection and recognition Rusing hybryd-information extracted from face space and facial features. Image and Vision Computing 23, 1181-1191.
  • BRUNELLI R. (2009) Template Matching Techniques in Computer Vision: Theory and Practice, Wiley.
  • CHEN S., ZHANG T., ZHANG Ch., CHENG Y. (2010) A real-time face detection and recognition system for a mobile robot in a complex background. Artif Life Robotics 15, 439-443.
  • CHIEN J.T. WU Ch.Ch. (2002) Discriminant Waveletface and Nearest Feature Classifiers for Face Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (12), 1644-1649.
  • GARCIA C., ZIKO, G., TZIRITAS G. (2000) Wavelet pocket analysis for face recognition. Image and Vision Computing 18, 289-297.
  • HJELMAS E., LOW B.K. (2001) Face Detection: A Survey. Computer Vision and Image Understanding 83, 236-274.
  • KANUNGO T. (1999) Hidden Markov Model Tutorial. www.kanungo.com/ software/hmmtut.pdf.
  • KIRBY M., SIROVICH L. (1990) Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces. IEEE Transaction on Pattern Analysis and Machine Intelligence, 12 (1), 103-108.
  • KOZUANI A.Z., HE F., SAMMUT K. (1997) Wavelet Packet Face Representation and Recognition. Proc. IEEE Conf. Systems, Man, and Cybernetics, NYC, 1614-1619.
  • KUBANEK M. (2006) Method of speech recognition and speaker identification with use audio-visual of polish speech and hidden markov models. In: K. Saeed, J. Peja, R. Mosdorf, eds., Biometrics, Computer Security Systems and Artificial Intelligence Applications. Springer Science + Business Media, 45-55.
  • KUKHAREV G., KUZMINSKY A. (2003) Techniki Biometryczne In: Metody Rozpoznawania Twarzy. Politechnika Szczecińska, Szczecin.
  • MISITI M., MISITI Y., OPPENHEIM G., POGGI J.-M. (2002) Wavelet Toolbox Users Guide. The MathWorks.
  • NABIYEV V., GAŚNAY A. (2008) Towards A Biometric Purpose Image Filter According To Skin Detection. Problems of Cybernetics and Informatics Conference, Baku, Azerbaijan. www.pci2008.science.az/2/17.pdf
  • RABINER L. R. (1989) A tutorial on hidden Markov models and selected application in speech recognition. Proc. IEEE 77, 257-285.
  • SAMARIA F, YOUNG S. (1994) HMM-based Architecture for Face Identification. Image and Vision Computing, 12, 8, 537-583.
  • VEZHNEVENTS V., SAZONOV V., ANDREEVA A.(2010) A Survey on Pixel Based Skin Color Detection Techniques, http://academic.aua.am/Skhachat/Public/Papers
  • YANG J., LING X., ZHU Y., ZHENG Z. (2008) A face detection and recognition system in color image series. Mathematics and Computers in Simulation 77, 531-539.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BATC-0011-0123
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