Objective Skin Typing Across the Spectrum: AI-Driven Fitzpatrick Classification from Facial Imagery

Accurate skin type classification is essential in dermatology and cosmetology, as skin tone plays a critical role in diagnostics, treatment, and product development. However, traditional Fitzpatrick assessment is often subjective and inconsistent, especially across diverse populations. This study presents an automated pipeline for Fitzpatrick skin type estimation from facial images. By combining deep facial segmentation with advanced color analysis techniques, this approach aims to enhance objectivity and inclusivity, supporting improvements in clinical diagnostics and personalized skincare.