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Design and implementation of liveness detection system based on improved shufflenet V2

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Abstract

Face recognition is a prevalent identity verification method, but it requires a liveness detection system to guard against face fraud from printed images and mobile phone photographs. It is challenging to guarantee low complexity and high accuracy of the face anti-spoofing model applied on the Android development board at the same time in existing research. On the Android development board, we construct a liveness detection system that is resistant to attacks from printed images and photographs of electronic devices such as tablets. In conjunction with the actual circumstance, we create a lightweight liveness detection algorithm based on near-infrared images. We utilize MTCNN to clip the near-infrared images in order to preserve the facial portions and reduce the calculated cost. After applying Gamma correction to weaken the impact of illumination on the faces, the facial images are subsequently incorporated into the enhanced ShuffleNet V2 model based on the MBConv and squeeze-excitation (SE) modules for secondary classification. We evaluate the performance of the enhanced model on the CBSR NIR Face Dataset, CASIA NIR-VIS 2.0 Face Database and Oulu-CASIA, achieving 98.50%, 99.87% and 100% accuracy, which is superior to the performance of the original ShuffleNet V2 model and state-of-the-art methods. Our model’s FLOPs and Params are 0.28 G and 2.17 M, respectively. Meanwhile, the liveness detection system based on Android has an exceptionally high level of security performance

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Funding

This work was supported by Science and Technology Planning Project of Guangdong Province under the grant 2018B010108001 and Key-Area Research and Development Program of Foshan City under the grant 2020001006812 and GuangDong Basic and Applied Basic Research Foundation under Grant 2022A1515110119.

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Authors and Affiliations

  1. School of Automation Science and Engineering, South China University of Technology, Guangzhou, 510641, China

    Yongxing Zhang & Wei Xie

  2. Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing, South China University of Technology, Guangzhou, 510640, China

    Wei Xie

  3. School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, 510006, China

    Xiaoyuan Yu

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  1. Yongxing Zhang
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  2. Wei Xie
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  3. Xiaoyuan Yu
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Correspondence to Wei Xie.

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Zhang, Y., Xie, W. & Yu, X. Design and implementation of liveness detection system based on improved shufflenet V2. SIViP 17, 3035–3043 (2023). https://doi.org/10.1007/s11760-023-02524-z

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