CNN Model for Analyzing Masked Facial RGB Images Using Cloud Computing

Abstract

The world invasion of dangerous virus diseases such as Covid 19, in the last few years, force people to wear masks as precaution. Although this prudence reduces the risk of infection and viruses’ spread, it adds difficulty to distinguishing or identifying a person. This paper proposes a method to analyze images of masked persons for classifying their gender, in addition to identifying the colors of their skin and their eyes. We apply residual learning using the convolutional neural network (CNN) based on the visible part of the face. Cloud computing resources have been used as a convenient environment of substantial computing ability. Also, new database of RGB face images was created for testing. Experiments have been operated on the constructed database beside other datasets of facial images after cropping. The proposed model gives 96% gender classification accuracy and 100% skin/eye color identification.