Abstract
Currently, facial recognition systems need to reveal a person’s face to perform recognition. However, some people currently wear masks to prevent respiratory infections. Therefore, this will affect the efficiency of some face recognition systems. Therefore, in this study, we propose a face recognition and body temperature measurement system, and propose an integrated system for masked face recognition, mask detection, and body temperature detection. The proposed system can be used to recognize unconcluded facial images, and we use methods capable of simulating occluded images. The resulting images are used to train the neural network. Experimental results show that the accuracy of naked face recognition reaches 99.79%, and the accuracy of masked face recognition reaches 99.4%. In addition, the mask detection accuracy rate reaches 99.6%. Therefore, the system can improve the accuracy of face recognition and provide efficient security inspection results.
Publisher
Granthaalayah Publications and Printers