Masked Face Detection Automation System using Mask Threshold and Viola Jones Method

Aminurachma Aisyah Nilatika; Khoerul Anwar; Eka Yuniar

doi:10.34288/jri.v5i1.185

Authors

Aminurachma Aisyah Nilatika STMIK PPKIA Pradnya Paramita
Khoerul Anwar STMIK PPKIA Pradnya Paramita
Eka Yuniar STMIK PPKIA Pradnya Paramita

(*) Corresponding Author

DOI:

https://doi.org/10.34288/jri.v5i1.185

Keywords:

Face detection, Masks, Mask tresholder, Segmentation, Viola jones Method

Abstract

Reducing or breaking the chain of Covid-19 virus infections during a pandemic is essential. The techniques encouraged are mandatory hand washing, social distancing, and wearing masks. Wearing masks is urgent. Therefore, requiring people to wear masks is the right policy. This study aims to detect people using or not using masks by applying the Viola-Jones method. This study modified the threshold algorithm by applying a masking threshold to optimize facial segmentation. Meanwhile, viola jones was built by combining several concepts of Haar Feature, Integral Image, AdaBoost, and classifier Cascade into the main method for detecting objects. The performance of the proposed method for face detection has an accuracy of 95%, a precision of 94.73%, and a recall of 100%. 5. The masked face detection test has an accuracy of 94%, a precision of 100%, and a recall of 90.90%

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