LZM in Action: Realtime Face Recognition System

  • Evangelos Sarıyanidi
  • Birkan Tunç
  • Muhittin Gökmen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7585)


In this technical demonstration, we introduce a real time face detection and recognition prototype. The proposed system can work with different image sources such as still images, videos from web cameras , and videos from ip cameras. The captured images are firstly processed by a cascaded classifier of Modified Census Transform (MCT) features to detect the faces. Then, facial features are detected inside the face region. These features are used to align and crop the face patches. Detection phase can be considerably improved by incorporating a tracking scheme to increase the hit rate while decreasing the false alarm rate. The registered faces are recognized using a novel method called Local Zernike Moments (LZM). A probabilistic decision step is employed in the final inference phase to provide a confidence margin. Introducing new identities via system’s user interface is considerably simple since the system does not require retraining after each new identity.


Face Recognition False Alarm Rate Face Detection Image Pyramid Face Tracking 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Fröba, B., Ernst, A.: Face detection with the modified census transform. In: Proceedings of the Sixth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 91–96. IEEE Computer Society, Washington, DC (2004)Google Scholar
  2. 2.
    Sarıyanidi, E., Tek, S.C., Gökmen, M.: Efficient face detection using coarse sampling. In: Conference on Signal Processing and Communications Applications (SIU), Turkey (2011)Google Scholar
  3. 3.
    Sarıyanidi, E., Dağlı, V., Tek, S.C., Tunç, B., Gökmen, M.: Local zernike moments: A new representation for face recognition. In: International Conference on Image Processing, ICIP (accepted, 2012)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Evangelos Sarıyanidi
    • 1
  • Birkan Tunç
    • 2
  • Muhittin Gökmen
    • 3
  1. 1.Control Engineering DepartmentIstanbul Technical UniversityTurkey
  2. 2.Informatics InstituteIstanbul Technical UniversityTurkey
  3. 3.Computer Engineering DepartmentIstanbul Technical UniversityTurkey

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