Abstract
It is quite challenging to localize noisy iris. In order to improve the stability and accuracy of noisy iris localization, this paper presents a statistical denoising integral difference operator (SDItg-Diff). Firstly, we use the Itg-Diff operator to produce several candidate boundaries with large Itg-Diff values. Then, the Pauta criterion is used to exclude the severe outlier pixels on each candidate boundary and the SDItg-Diff indicator is calculated after noise removal. The boundary with the max SDItg-Diff indicator is taken as the final localization boundary. The experimental result shows that, compared with the Itg-Diff operator, the proposed method can achieve more stable localization on noisy iris images.
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Acknowledgement
This work is supported by National Natural Science Funds of China, No. 11371081 and No. 61703088, the Doctoral Scientific Research Foundation of Liaoning Province, No.20170520326 and “the Fundamental Research Funds for the Central Universities”, N160503003.
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Zhang, X., Zhou, R., Meng, X., Wang, Q. (2019). SDItg-Diff: Noisy Iris Localization Based on Statistical Denoising. In: Sun, Z., He, R., Feng, J., Shan, S., Guo, Z. (eds) Biometric Recognition. CCBR 2019. Lecture Notes in Computer Science(), vol 11818. Springer, Cham. https://doi.org/10.1007/978-3-030-31456-9_40
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DOI: https://doi.org/10.1007/978-3-030-31456-9_40
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