Face Mask Detection Using Convolutional Neural Network (CNN)

EasyChair Preprint 6987

Abstract

COVID-19 pandemic has rapidly affected our day-to-day life disrupting the world trade and movements. Wearing a face mask for Protection  has become a new normal. Face detection and recognition will be considered as one of the most intriguing modalities for biometric models. Therefore, face mask detection has become a crucial task to help global society.For this purpose we are using some basic Machine Learning packages like TensorFlow, Keras, OpenCV and Scikit-Learn. Here, in this Project a very fast image pre-processing with the mask in the center over the faces.Our Model is trained on dataset that consists of images of people of two categories that are with and without face masks.Three levels of work that  we carried out are: images preprocessing, extracting crucial part from images and image classification. Features extraction and Convolutional Neural Network are used for classification and detection of a masked person. This Method attain an accuracy of 99.1 %.

Keyphrases: CNN, HaarCascade, OpenCV

@booklet{EasyChair:6987,
  author    = {Udit Upadhyay and Bhawna Rudra and Udit Upadhyay},
  title     = {Face Mask Detection Using Convolutional Neural Network (CNN)},
  howpublished = {EasyChair Preprint 6987},
  year      = {EasyChair, 2021}}