Feature correlation evaluation approach for iris feature quality measure

Authors:
Yingzi Du;Craig Belcher;Zhi Zhou;Robert Ives
Affiliations:
Department of Electrical and Computer Engineering, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA;Department of Electrical and Computer Engineering, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA;Department of Electrical and Computer Engineering, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA;Department of Electrical Engineering, U.S. Naval Academy, USA
Venue:
Signal Processing
Year:
2010

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Abstract

It is challenging to develop an iris image quality measure to determine compressed iris image quality. The compression process introduces new artificial patterns while suppressing existing iris patterns. This paper proposes a feature correlation evaluation approach for iris image quality measure, which can discriminate the artificial patterns from the natural iris patterns and can also measure iris image quality for uncompressed images. The experimental results show that the proposed method could objectively perform quality measure on both non-compressed and compressed images.