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Shuqin Gao

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Proceedings Article | 10 April 2018 Paper

The fast iris image clarity evaluation based on Tenengrad and ROI selection

Shuqin Gao, Min Han, Xu Cheng

Proceedings Volume 10615, 106154X (2018) https://doi.org/10.1117/12.2302509

KEYWORDS: Iris recognition, Iris, Image analysis, Image processing, Detection and tracking algorithms, Biometrics, Image acquisition, Information science, Reliability

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In iris recognition system, the clarity of iris image is an important factor that influences recognition effect. In the process of recognition, the blurred image may possibly be rejected by the automatic iris recognition system, which will lead to the failure of identification. Therefore it is necessary to evaluate the iris image definition before recognition. Considered the existing evaluation methods on iris image definition, we proposed a fast algorithm to evaluate the definition of iris image in this paper. In our algorithm, firstly ROI (Region of Interest) is extracted based on the reference point which is determined by using the feature of the light spots within the pupil, then Tenengrad operator is used to evaluate the iris image’s definition. Experiment results show that, the iris image definition algorithm proposed in this paper could accurately distinguish the iris images of different clarity, and the algorithm has the merit of low computational complexity and more effectiveness.

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