At-home rapid antigen test (RAT) kits for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are valuable public health tools during the present coronavirus disease (COVID-19) pandemic. They provide fast identification of coronavirus infection, which can help to reduce the transmission rates and burden on the healthcare system. However, they have lower sensitivity compared to the reverse transcription polymerase chain reaction (RT-PCR) tests. One of the reasons for the lower sensitivity is due to the RAT color indicators being indistinct or invisible to the naked eye after the measurements. For this reason, we present a proof of concept of a novel approach, through which we investigated anonymously provided at-home RAT kit results by using our in-house open-source image processing scripts developed for affordable Raspberry Pi computer and Raspberry Pi HQ camera systems. Therefore, we aimed at minimizing the human-related analysis errors for such kits and believe that the present computer vision-based assessment framework can contribute to reducing delayed quarantines of infected individuals and the spread of the current infectious disease.