A Machine Learning Approach to Identifying Facial Masks in Real Time
Charu Khosla Gupta, Sakshi Rawat, Narendra Kumar · 2023
Face masks became a necessity since the outbreak of COVID-19 as a way to avoid the spread, especially in crowded places, and are counted as one of the most effective methods to control the spread. However, some people are frivolous and avoid wearing a face mask. But when we are in public places or places attracting a huge crowd, monitoring such people manually or identifying them through constant surveillance is a hectic task and requires strenuous efforts, which is why real-time face mask detection is in such high demand. The main objective of this paper is to introduce real-time face mask detection techniques, which are based on real-time analysis and detect whether someone is wearing a mask or not. It is quite challenging, as we have used different types of machine learning algorithms for face detection and then for face detection with a mask. It is important to have a good dataset that has less noise and minimum errors in order to train the model and have high accuracy in our results. This is difficult because the dataset must be cleaned, sorted, and data with incorrect labels removed. The Open-CV Python library, Keras, and TensorFlow are used in this paper for better results.