Pigment-Aware: Understanding Skin Tone Variations in Digital Image Analysis

Optical sensors, such as the RGB cameras embedded in smartphones, often fail to accurately capture the full spectrum of skin tones. As a result, individuals with darker skin may experience reduced performance in machine vision-based security systems. Insufficient attention to human diversity, including variations in skin tone, can contribute to biased training data and, subsequently, to disparities in AI systems, especially in biometric recognition. This paper highlights the need for more consistent and objective approaches to assessing skin tone, which are often treated subjectively or applied inconsistently. We address this issue by analyzing RGB finger photo data using colorimetric techniques to support the development of more inclusive machine vision systems.