Detection system of facial patterns with masks in new normal based on the Viola Jones method. Issue 1 (March 2021)

• Record Type: Journal Article
• Authors: Jauhari, A; Anamisa, D R; Negara, Y D P
• Is Part Of: Journal of physics. Volume 1836:Issue 1(2021)
• Publication Date: 2021-03
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1836/1/012035
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Covid-19 is something that was never expected, it can turn into an endemic virus in the community. There is a possibility that this virus will not be completely destroyed. This makes the world and Indonesia in an uncomfortable position. Two months with Social Distancing conditions, the Government of Indonesia has been preparing to roll back the sluggish economic wheel as a result of the implementation of Social Distancing. Therefore, the Indonesian people must live in peace with Covid-19 until the discovery of an effective vaccine. This condition is called new normal. This study designed a detection system of facial patterns using masks during the pandemic based on Real-Time Raspberry. The purpose of detecting face patterns by using a mask is to find out if there are masked faces in the image. Although it seems easy to do by humans, it turns out that this detection system is difficult to do without the help of a computer to process facial recognition because there are some difficulties related to location, point of view, light, and occlusion. This research has implemented a detection system using the Viola Jones method. Viola Jones method is a method to get fast, accurate and efficient results in face detection on images. This study using the Viola Jones method to adjust the threshold value, and form the Cascade Classifier in determining the face area in the image. This training can be evaluated the accuracy of the system by modifying the parameter values in the Viola Jones method so that this design can produce the highest accuracy for face images using masks and low accuracy for face images without using masks. From the results of trials with 100 face samples, the accuracy percentage is 90.9% and it takes a relatively short time to detect faces using a mask that is on average 15 seconds per sample tested.