Abstract
There are few restrictions in the image capture of mobile iris recognition, so the iris texture is easily interfered and the images may fail to meet the requirements of the identification. If the quality of captured iris images can be pre-evaluated, the unrecognizable iris images could be removed, which can reduce the operational burden and be more efficient. Therefore, an approach for iris image quality assessment based on saliency detection is proposed in this paper. First, Frequency-tuned (FT) method is used to detect image salient regions, then the binary image is obtained by segmenting saliency maps with threshold, and finally the image quality is evaluated according to the shape characteristics of the connected regions in binary images. As the results shown, the proposed method is capable of evaluating the image quality under the ideal and disturbing conditions, and removing the unrecognizable iris images because of the interference.
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All the images are from the dataset MICHE, all rights reserved.
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Liu, X., Luo, Y., Yin, S., Gao, S. (2016). Iris Image Quality Assessment Based on Saliency Detection. In: You, Z., et al. Biometric Recognition. CCBR 2016. Lecture Notes in Computer Science(), vol 9967. Springer, Cham. https://doi.org/10.1007/978-3-319-46654-5_38
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DOI: https://doi.org/10.1007/978-3-319-46654-5_38
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