Research on 3D fingerprint structure recognition based on OCT system

Wang Liu; Zhaowei Zhong; Zhifang Li; Yongping Lin; Hui Li

doi:10.1117/12.2549931

12 March 2020 Research on 3D fingerprint structure recognition based on OCT system

Wang Liu, Zhaowei Zhong, Zhifang Li, Yongping Lin, Hui Li

Proceedings Volume 11434, 2019 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments; 1143417 (2020) https://doi.org/10.1117/12.2549931
Event: 2019 International Conference on Optical Instruments and Technology, 2019, Beijing, China

Abstract

The most widely used fingerprint recognition technology is to extract the texture information and features of the skin fingerprint, and then use the algorithm to match and identify, and finally confirm the identity. However, when there are dirt and water stains on the fingerprint of the skin, or when the fingerprint skin is worn or even peeled off, the generation of these factors will bring difficulties to the identification system. In this study, optical coherence tomography (OCT) was used to obtain the three-dimensional structure of the finger fingerprint, and the three-dimensional structure inside the fingerprint was identified. The three-dimensional structure image of the fingerprint obtained by the OCT system can not only observe the fingerprint skin information, but also acquire the image information of the internal structure of the fingerprint. Taking the acquired three-dimensional structure image of fingerprint as the research object, a three-dimensional convolutional neural network model is constructed based on the theory of deep learning, and the features of image data is extracted and trained to achieve the purpose of recognition.

Citation Download Citation

Wang Liu, Zhaowei Zhong, Zhifang Li, Yongping Lin, and Hui Li "Research on 3D fingerprint structure recognition based on OCT system", Proc. SPIE 11434, 2019 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments, 1143417 (12 March 2020); https://doi.org/10.1117/12.2549931

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KEYWORDS

3D image processing

Fingerprint recognition

Optical coherence tomography

Convolution

3D modeling

Skin

Convolutional neural networks

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