A comprehensive approach for sclera image quality measure

  • Authors:

  • Zhi Zhou;Eliza Y. Du;N. Luke Thomas;Edward J. Delp

  • Affiliations:

  • Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46214, USA;Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46214, USA;Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46214, USA;School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA

  • Venue:
  • International Journal of Biometrics
  • Year:
  • 2013

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Abstract

Poor quality images can affect sclera recognition accuracy. An image quality measure can help improve the recognition system performance. In this paper, we proposed a comprehensive approach for sclera image quality measure, which includes quality filter and quantitative quality assessment unit, segmentation evaluation unit, feature evaluation unit, and score fusion unit. The experimental results show that the combination score is highly correlated with the sclera recognition accuracy and can be used to improve and predict the performance of sclera recognition systems.