关键词: 虹膜识别, 虹膜图像质量评价, 离焦模糊

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 relationship 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.

Key words: iris recognition, iris image quality assessment, defocus