Abstract
Non-contact biometric identification technology is once again receiving social attention these days when untact technology is required due to the Covid-19. Face recognition technology is being used in a variety of platforms such as airport immigration systems, hospital patient management systems, financial self-authentication systems, criminal suspect detection systems, and personal authentication systems for mobile devices, and is showing its effectiveness. In this paper, multiple face recognition technology is applied to the automatic attendance system. Unlike when only one person is recognized, multiple face recognition results in lower accuracy and slower processing speed. In this paper, a frontal face detection algorithm is proposed. Using the frontal face detection algorithm, only the frontal face was used for recognition, and when 36 people were recognized, 97.2% accuracy was achieved. In addition, we proposed an erasing multiple face recognition method and increased the average number of frames processed per second as the recognition completion rate increased.
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