Pilot Iris Recognition Based on Spherical Haar Wavelet and Convolutional Neural Network

Bo JIA; Xiaoxin FENG; Jun LI; Biting YU; Qian ZHAO; Qi WU

doi:10.11999/JEIT190928

Volume 43 Issue 4

Apr. 2021

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Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(4): 939-947

Bo JIA, Xiaoxin FENG, Jun LI, Biting YU, Qian ZHAO, Qi WU. Pilot Iris Recognition Based on Spherical Haar Wavelet and Convolutional Neural Network[J]. Journal of Electronics & Information Technology, 2021, 43(4): 939-947. doi: 10.11999/JEIT190928

Citation:

Bo JIA, Xiaoxin FENG, Jun LI, Biting YU, Qian ZHAO, Qi WU. Pilot Iris Recognition Based on Spherical Haar Wavelet and Convolutional Neural Network[J]. Journal of Electronics & Information Technology, 2021, 43(4): 939-947. doi: 10.11999/JEIT190928

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Pilot Iris Recognition Based on Spherical Haar Wavelet and Convolutional Neural Network

doi: 10.11999/JEIT190928

Bo JIA¹,
Xiaoxin FENG²,
Jun LI¹,
Biting YU³,
Qian ZHAO¹,
Qi WU^{2
,
,}

1.
China Eastern Technology Application R&D Center Co.Ltd., Shanghai 201707, China
2.
School of Electronic, Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
3.
University of Wollongong, Wollongong 2500, Australia

Funds: The National Natural Science Foundation of China (U1933125)

Received Date: 2019-11-20
Rev Recd Date: 2021-01-15

Available Online: 2021-01-22

Publish Date: 2021-04-20

Abstract

Abstract

Iris recognition faces two important issues. they are how to decompose finely and reconstruct the spherical image of the iris, and how to identify the characteristics of the iris. Conventional iris recognition uses usually the planar features of these iris images. However, the human eye is a sphere. The geometric position information of the iris surface is an important signal, but it is difficult to extract the geometric features of the iris sphere from the planar image. Considering the issue that the plane features are prone to distortion and lack fidelity of iris texture, an Orthogonal and Symmetric Spherical Haar Wavelet (OSSHW) basis is proposed to decompose and reconstruct the spherical iris signal to obtain stronger geometric features of iris surface. The comparison of the feature extraction ability to spherical signal by the spherical harmonics and the typical semi-orthogonal or nearly orthogonal spherical Haar wavelet is also presented. And then, an iris recognition method based on Convolutional Neural Networks (CNN) + OSSHW is proposed, which can effectively capture the local fine features of iris spherical surface, and has stronger ability in iris recognition than semi-orthogonal or nearly orthogonal spherical Haar wavelet bases.
- Iris recognition,
- Spherical Haar wavelet basis,
- Spherical signals,
- Orthogonal and symmetric

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References(17)

References

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