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Coronavirus Disease 2019 (COVID-19) has spread all over the world since itbroke out massively in December 2019, which has caused a large loss to thewhole world. Both the confirmed cases and death cases have reached a relativelyfrightening number. Syndrome coronaviruses 2 (SARS-CoV-2), the cause ofCOVID-19, can be transmitted by small respiratory droplets. To curb its spreadat the source, wearing masks is a convenient and effective measure. In mostcases, people use face masks in a high-frequent but short-time way. Aimed atsolving the problem that we don't know which service stage of the mask belongsto, we propose a detection system based on the mobile phone. We first extractfour features from the GLCMs of the face mask's micro-photos. Next, athree-result detection system is accomplished by using KNN algorithm. Theresults of validation experiments show that our system can reach a precision of82.87% (standard deviation=8.5%) on the testing dataset. In future work, weplan to expand the detection objects to more mask types. This work demonstratesthat the proposed mobile microscope system can be used as an assistant for facemask being used, which may play a positive role in fighting against COVID-19.

Face Mask Assistant: Detection of Face Mask Service Stage Based on Mobile Phone