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Volume 43 Issue 9
Sep.  2021
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HUANG Jun, ZHANG Nana, ZHANG Hui. Silent Live Face Detection in Near-Infrared Images Based on Optimized LeNet-5[J]. Infrared Technology , 2021, 43(9): 845-851.
Citation: HUANG Jun, ZHANG Nana, ZHANG Hui. Silent Live Face Detection in Near-Infrared Images Based on Optimized LeNet-5[J]. Infrared Technology , 2021, 43(9): 845-851.
shu

Silent Live Face Detection in Near-Infrared Images Based on Optimized LeNet-5

  • 1.

    College of Information Technology, Shanghai Ocean University, Shanghai 201306, China

  • 2.

    College of Information Technology, Shanghai Jian Qiao University, Shanghai 201306, China

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  • Received Date: November 30, 2020
  • Revised Date: January 19, 2021
    Graphical Abstract
    • Abstract
  • An improved method of silent liveness detection for LeNet-5 and near-infrared images is proposed to overcome the problem of the interactive liveness detection process and poor user experience. First, a face attack dataset was constructed using a near-infrared camera. Second, the LeNet-5 was optimized by increasing the number of convolution kernels and introducing global average pooling to construct a deep convolutional neural network. Finally, the near-infrared face image is input to the model to realize silent liveness detection. The experimental results show that the proposed model has a higher recognition rate for the liveness detection dataset, reaching 99.95%. The running speed of the silent liveness detection system is approximately 18-22 frames per second, which shows high robustness in practical applications.
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    • References (15)
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