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Joint Masked Face Recognition and Temperature Measurement System Using Convolutional Neural Networks.

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This study introduces an automated attendance system using masked face recognition and thermal imaging cameras to simultaneously record body temperature and identify individuals. The system achieves 94.1% accuracy, enhancing epidemic prevention in public spaces.

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deep learningembedded systemface detectionmasked face recognition

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Area of Science:

  • Computer Science
  • Biomedical Engineering
  • Public Health

Background:

  • The COVID-19 pandemic necessitates effective epidemic prevention measures in public spaces.
  • Non-contact body temperature measurement using thermal imaging cameras is crucial for infection risk reduction.
  • Traditional face recognition systems struggle with accuracy due to mandatory mask-wearing.

Purpose of the Study:

  • To develop an automated attendance system integrating masked face recognition and thermal imaging.
  • To simultaneously record body temperature and identify individuals, reducing infection transmission risks.
  • To provide a practical, embedded system solution for real-world epidemic prevention scenarios.

Main Methods:

  • Utilized convolutional neural networks (CNNs) for masked face recognition algorithm design.
  • Integrated thermal imaging cameras for non-contact body temperature measurement.
  • Developed a user interface (UI) system for attendance information management and retrieval.

Main Results:

  • Achieved a 94.1% accuracy rate for masked face recognition in real-world testing.
  • Successfully demonstrated a complete embedded system for automated attendance and temperature screening.
  • Enabled simultaneous recording of body temperature and personal identification.

Conclusions:

  • The combined system effectively addresses the challenge of masked face recognition for attendance.
  • This integrated approach enhances epidemic prevention by facilitating temperature screening at entry points.
  • The developed system offers a practical solution for automated, contactless attendance and health monitoring.