A Human Skin Diagnosis System Using Human Skin Reflective Spectrum Matching

Recently, the beauty market demands easier and more accurate skin diagnosis methods that can diagnose skin in a non-contact manner. In this study, we proposed a noncontact skin diagnosis method to evaluate personal skin information through mechanical matching of simulated optical skin reflection spectrum based on the Kubelka-Munk 2-layer model with actually measured skin reflection spectrum. For the validation of this skin information, correlation analysis between the spectrum matched skin information and the actually measured skin information was performed. Results confirmed that the spectrum matched skin information (melanin, hemoglobin, and dermis thickness) had a strong correlation with the actually measured skin information in terms of statistical significance.