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| A Quality Assessment Method of Iris Image Based on Support Vector Machine |
| Si Gao, Xiaodong Zhu, Yuanning Liu, Fei He, Guang Huo |
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Abstract The quality of iris image is one of the key factors influences the
performance of iris pattern recognition. Based on the existing
quality assessment measures of iris image, and in consideration of
the most prominent factors that lead recognition to fail, we
firstly put forward iris rotation which is a new quality assessment
measure. Then Iris Rotation, Iris Visibility, Iris Eccentricity and
Iris Definition are together as quality assessment measures of iris
image and the quality assessment of iris image is done by Support
Vector Machine (SVM) classifier. The experiment results express that
the method we propose can select the images with good quality and
has strong predictability for the performance of iris pattern
recognition.
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| Cite this article: |
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Si Gao,Xiaodong Zhu,Yuanning Liu, et al. A Quality Assessment Method of Iris Image Based on Support Vector Machine[J]. Journal of Fiber Bioengineering and Informatics, 2015, 8(2): 293-300.
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2015, Vol. 8 
