Abstract: Detecting masked and non-masked faces are increasingly very crucial since wearing a face mask is an effective measure to prevent the spread of the COVID-19 pandemic. COVID-19 pandemic has rapidly increased health crises all over the world and is affecting our everyday lifestyle. The only motive for survival recommendations is to wear a safe facemask, stay protected against the spread of covid-19. Monitoring if the individuals are wearing facemask properly and to notify the victim in public and crowded areas is a very difficult task. This paper approaches a simplified way to achieve facemask detection and notifying the individual person if he is not wearing facemask. Face detection and recognition will be considered as one of the most intriguing modalities for biometric models. For this system, features extraction and Convolutional Neural Network are used for classification and detection of a person who is wearing the mask. This research work will be carried out in three levels: preprocessing the images, cropping the images and classification of the images. This helps to detect whether the face is masked or not. A webcam or CCTV camera surveillance will record all the timings and it checks whether the person is wearing a mask or not, if the person doesn’t wear a mask, then the system will give a security alert.
Keywords: Transforming CNN, Features extraction, Images classification
Copyright Form