Abstract
Measuring skin color for medical research in an objective and nonbiased manner usually requires expensive equipment such as spectrophotometry and requires the subject to be present in person. We present a novel method to measure skin color from photographs using the Skin Analyzer application as a more effective, accessible, and efficient alternative. A desktop application, the Skin Analyzer, was developed to convert skin samples collected from digital images to the L*a*b color space and uses those values to calculate an individual typology angle that correlates to a Fitzpatrick skin type. To assess accuracy in variable lighting, six known colors representing the six Fitzpatrick skin types were printed and photographed in 15 separate locations within the hospital. To account for user variability in sample selection, interrater reliability was calculated with data generated by 13 untrained users testing the app on six subjects. The accuracy of measuring known values, which is the classification accuracy, was calculated to be 80%. Krippendorff alpha test was used to evaluate interrater reliability. The obtained alpha of 0.84 indicates a high interrater reliability. The high accuracy and reliability make the Skin Analyzer a suitable method of objectively determining Fitzpatrick skin type from images. The app may be used to investigate the effects of skin tone in various areas of interest, especially in retrospective studies where skin colorimeters cannot be used.