Face Mask Detection Using Machine Learning

Abstract

COVID-19 epidemic has affected our daily life disturbing the world trade and transport. Wearing a face mask has become a new necessity for safety. In the near future, many institutions will ask the customers to wear masks to avail of their services. Therefore, face mask detection has become a necessity to help society. This paper presents a simplified approach to achieve this purpose using some packages like TensorFlow, Keras, OpenCV and Scikit-Learn. This method detects the face from the image in frame and then identifies if it has worn a mask or not. As in a surveillance task, it can also detect a face along with a mask in movement through image processing. The method attains accuracy up to 93% and 91.2% respectively on two datasets. We explore optimized values of parameters using the Sequential CNN (Convolutional Neural Network) model to detect the presence of masks correctly. Keywords: Face Mask Detection, Convolutional Neural Network, TensorFlow, Keras, Image Processing