Face Mask Wearing Detection using Independent Component Analysis and Naïve Bayes Classifier

Q4 Biochemistry, Genetics and Molecular Biology

International Journal of Biology and Biomedical Engineering Pub Date : 2022-05-04 DOI:10.46300/91011.2022.16.33

A.M. Mansour

引用次数: 0

Abstract

In this paper, a new method was developed to detect the face mask wearing conditions using both Independent Component Analysis as a feature extractor and naïve Bayes as a classifies. The method was tested using real face images. The dataset was used for both training and testing. The MATLAB is used as programming software. The achieved accuracy in the testing 92.67%. The method was also tested using real live face pictures. The results were excellent, and the accuracy was 87.29%.

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基于独立分量分析和朴素贝叶斯分类器的口罩佩戴检测

在本文中，开发了一种新的方法来检测口罩佩戴情况，使用独立分量分析作为特征提取器，使用朴素贝叶斯作为分类。该方法使用真实人脸图像进行了测试。该数据集用于训练和测试。使用MATLAB作为编程软件。该方法的测试准确率为92.67%。该方法还使用真实的人脸照片进行了测试。结果优良，准确率为87.29%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Biology and Biomedical Engineering Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)

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期刊介绍： Topics: Molecular Dynamics, Biochemistry, Biophysics, Quantum Chemistry, Molecular Biology, Cell Biology, Immunology, Neurophysiology, Genetics, Population Dynamics, Dynamics of Diseases, Bioecology, Epidemiology, Social Dynamics, PhotoBiology, PhotoChemistry, Plant Biology, Microbiology, Immunology, Bioinformatics, Signal Transduction, Environmental Systems, Psychological and Cognitive Systems, Pattern Formation, Evolution, Game Theory and Adaptive Dynamics, Bioengineering, Biotechnolgies, Medical Imaging, Medical Signal Processing, Feedback Control in Biology and Chemistry, Fluid Mechanics and Applications in Biomedicine, Space Medicine and Biology, Nuclear Biology and Medicine.