Abstract
BACKGROUND: Skin barrier function is significantly impacted by skin moisture. Most non-invasive evaluation techniques to measure skin surface hydration relying on its electrical properties, which are limited in scope and have unstable operations. Applying image processing for skin hydration assessment is uncommon, with an emphasis on skin-capacitive pictures and near-infrared images in general, which demand a certain spectrum. As a result, there is an increasing need for wide-area skin hydration evaluation and mapping. OBJECTIVE: The study aims to propose a quantitative evaluation algorithm for skin surface hydration from visible-light images. MATERIALS AND METHODS: Three devices were applied to measure skin hydration: skin image capture device and two recognized commercial skin devices. A digital image processing system creates a new index, called GVR, to symbolize skin surface moisture. The CLAHE algorithm was applied to enhance the contrast of skin image, and after calculating it with the monochrome image, the skin reflectance image was segmented. The GVR was estimated using the values of the individual sites and the entire skin. The correlation coefficient between the three methods was examined using statistical analysis to assess the performance of GVR. RESULTS: Skin hydration estimated from visible-light images is influenced by the entire facial structure in addition to specific areas. The electrical and visible image evaluations showed a strong association with a significant difference. CONCLUSION: It was discovered that reflecting measures from visible images provide a quick and efficient way to quantify the moisture of the skin's surface.