Skin Detection Through Hyperspectral Imaging

Skin detection plays a crucial role in various applications, ranging from biometric recognition and comfort management to the realization of intelligent and adaptive environments. It is an important component in Human-Machine Systems, enabling seamless interaction between individuals and smart environments. In this context, skin detection is particularly relevant for providing rich context information that can be exploited to dynamically optimize environmental conditions and improve user experience. In this paper, we introduce a Hyperspectral Imaging (HSI)-based approach to distinguish human skin from other materials in smart environments. Our method reliably extracts spectral signatures of human skin, even under non-standard and uncontrolled conditions, enabling robust and non-invasive skin recognition. To validate our approach, we applied it to publicly available multispectral image datasets. The results of our study promote the development of multispectral-based sensing systems, strengthening the role of spectral imaging in the implementation of smart environments.