Is Face Recognition with Masks Possible?

Yaaseen Muhammad Saib,Sameerchand Pudaruth

doi:10.14569/ijacsa.2021.0120706

Yaaseen Muhammad Saib, Sameerchand Pudaruth

Open Access

https://doi.org/10.14569/ijacsa.2021.0120706

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Abstract

With the recent outbreak of the COVID-19 pandemic, wearing face masks has become extremely important to protect us, and to reduce the spread of the virus. This measure has made many existing face recognition systems ineffective as they were trained to work with unmasked faces. In this paper, several methods have been proposed for masked face recognition. Two pre-trained deep learning architectures (VGG16, and MobileNetV2) and the Histogram of Gradients (HOG) technique were used to extract the relevant features from face images of celebrities. A SoftMax layer and Support Vector Machines (SVM) were used for classification. Five scenarios were devised to assess the different models and approaches. With an accuracy of 96.8%, the best model was obtained with MobileNetV2 with a SoftMax layer on the dataset consisting of a mixture of masked and unmasked images. Three different types of masks were also used in this study. The mean accuracy was 91.35% when the same type of mask is used for training and testing. However, the accuracy dropped by an average of 5.6% when a different type of mask is used for training and testing. A contactless attendance system using the best masked face recognition model has also been implemented. © 2021. All Rights Reserved.

Highlights

There are several biometric systems available that can be used to secure access to data but in this work, the focus is on face recognition systems
Blokdyk explained the main processes in the face recognition system: face detection, feature extraction and classification [3]
Several tests were performed with different scenarios and the average face recognition rate achieved was 90%

Summary

Introduction

There are several biometric systems available that can be used to secure access to data but in this work, the focus is on face recognition systems. Symanovich defined face recognition as the process of using the face of an individual from a photo or video to verify their identity [1]. Klosowski explained how this technology is being used around the world for many purposes such as unlocking mobile phones and laptops, monitoring people’s physical access to restricted areas such as high-tech laboratories or even taking attendance in lectures [2]. The process of taking an image and locating the region that contains the face only is known as face detection This region is stored as a set of coordinates representing a bounding box around the detected faces. This is a very challenging task since faces in different images have many variations with regards to facial expressions, pose, degree of occlusions and lighting conditions [4]

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