Developing a predictive model of human skin coloring

Symon Cotton; Ela Claridge

doi:10.1117/12.237846

11 April 1996 Developing a predictive model of human skin coloring

Symon Cotton, Ela Claridge

Proceedings Volume 2708, Medical Imaging 1996: Physics of Medical Imaging; (1996) https://doi.org/10.1117/12.237846
Event: Medical Imaging 1996, 1996, Newport Beach, CA, United States

Abstract

A model of color formation within human skin has been developed to aid the characterization of pigmented skin lesions from their digitized color images. The model is based on the Kublenka-Munk theory of scattering and absorption within inhomogeneous materials and the physics pertaining to their color properties. By considering the skin to be a layered construction of such materials, the stratum corneum, epidermis, papillary dermis and reticular dermis, and by exploiting the physics related to the optical interface between these layers, the model generates all possible colors occurring within normal human skin. In particular, the model predicts that all skin colors have to lie on a simple curved surface patch within a three- dimensional color space bounded by two physiologically meaningful axes, one corresponding to the amount of melanin within the epidermis and the other to the amount of blood within the dermis. These predictions were verified by comparing the CIE LMS coordinates of a representative, cross-racial sample of fifty skin images with the LMS coordinates predicted by the model. The results show that, within the predicted error bounds, the coordinates for normal skin colors do indeed lie on the curved surface generated by the model. Several possible applications of this representation are outlined, including images representing the melanin and blood components separately, as well as the possibility of measuring the Breslow thickness of melanocytic invasion within malignant melanoma.

Citation Download Citation

Symon Cotton and Ela Claridge "Developing a predictive model of human skin coloring", Proc. SPIE 2708, Medical Imaging 1996: Physics of Medical Imaging, (11 April 1996); https://doi.org/10.1117/12.237846

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