计算机科学与探索Issue(1)：81-89,9.DOI:10.3778/j.issn.1673-9418.1306020
由粗到精的虹膜图像离焦模糊评价方法
Coarse to Fine Defocus Assessment of Iris Images
摘要
Abstract
Defocus assessment of iris images is crucial for iris recognition system. Traditionally, the spectral power in high frequency band is adopted to measure the iris image quality. However, these methods are easily affected by the illumination variation and outlier regions in iris images, such as eyelash or eyelid regions. This paper proposes a two-step framework for the iris image defocus assessment. In the first step, the traditional iris image defocus metric is introduced to identify severely defocus iris images. In the second step, the quality features of iris images based on steerable pyramid decomposition are extracted. Then, the radial basis network is adopted to formulate the relation-ship between iris image quality features and iris image quality levels on the synthetic database. Finally, the model trained on the synthetic database is directly used to predict the iris image quality. The experimental results conducted on Clarkson database demonstrate that the proposed iris image defocus assessment method not only distinguishes the clear ones from the defocus iris images, but also is more relevant to perceptual quality than state-of-the-art methods.关键词
虹膜识别/虹膜图像质量评价/离焦模糊Key words
iris recognition/iris image quality assessment/defocus分类
信息技术与安全科学引用本文复制引用
李星光,孙哲南,谭铁牛..由粗到精的虹膜图像离焦模糊评价方法[J].计算机科学与探索,2014,(1):81-89,9.基金项目
The National Natural Science Foundation of China under Grant No.61075024(国家自然科学基金面上项目) （国家自然科学基金面上项目）
