Measurement of Defocus Level in Iris Images Using Different Convolution Kernel Methods

  • J. Miguel Colores-Vargas
  • Mireya S. García-Vázquez
  • Alejandro A. Ramírez-Acosta
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6256)


During the video and fixed image acquisition procedure of an automatic iris recognition system, it is essential to acquire focused iris images. If defocus iris images are acquired, the performance of the iris recognition is degraded, because iris images don’t have enough feature information. Therefore it’s important to adopt the image quality evaluation method before the image processing. In this paper, it is analyzed and compared four representative quality assessment methods on the MBGC iris database. Through methods, it can fast grade the images and pick out the high quality iris images from the video sequence captured by real-time iris recognition camera. The experimental results of the four methods according to the receiver operating characteristic (ROC) curve are shown. Then the optimal method of quality evaluation that allows better performance in an automatic iris recognition system is founded. This paper also presents an analysis in terms of computation speed of the four methods.


Convolution kernel defocus iris quality video 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • J. Miguel Colores-Vargas
    • 1
  • Mireya S. García-Vázquez
    • 1
  • Alejandro A. Ramírez-Acosta
    • 2
  1. 1.Instituto Politécnico Nacional-CITEDITijuana
  2. 2.MIRAL R&DImperial BeachUSA

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