This research suggests a color constancy algorithm using the human sclera and pupil for estimating skin color. The human sclera is approximately white, reflecting the hue characteristics of the illuminant. On the contrary, the pupil is shown as approximately black, independently of the surroundings. Consequently, the sclera and pupil account for the color characteristics of a facial image. Based on this assumption, a new color constancy algorithm was developed, and we examined the performance by comparing the calibrated colors with actual skin colors measured with a spectrophotometer. As the dataset, we collected facial images as well as the CIEL*a*b* values of 348 Korean females. As a result, the error of the proposed algorithm was significantly smaller than the state-of-art skin estimation algorithms. The algorithm developed in this study provides evidence that the human sclera and pupil successfully serve as the calibration targets to estimate the color of human skin.
Hayan Choi, Kyungah Choi, Hyeon-Jeong Suk, "The human sclera and pupil as the calibration targets" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Computational Imaging XV, 2017, pp 200 - 203, https://doi.org/10.2352/ISSN.2470-1173.2017.17.COIMG-448