Research Techniques Made Simple: Cutaneous Colorimetry: A Reliable Technique for Objective Skin Color Measurement

Abstract

Skin color evaluation contributes to assessment of an individual's cutaneous phenotype. Skin color changes provide important clues to disease progression or treatment response. Skin color is also a predictor of skin cancer risk. Melanin pigment, blood flow, skin thickness, and photoaging contribute to skin color. Melanin, hemoglobin, bilirubin, and carotene are the primary chromophores of skin color. Their concentrations vary depending on the individual's phenotype, anatomic location, external insults of chemical irritants and UVR, and physiological changes. The evaluation and perception of skin color are often subjective. Objective quantification of skin color can be achieved with colorimetric devices such as tristimulus colorimeters. These devices compute the intensity of light reflected from skin and correlate with pigmentation and erythema. Cutaneous color and color changes can be quantified under color organization systems, such as the CIELAB color space, which is standardized by the Commission Internationale de l'Eclairage (CIE). The CIELAB expresses color's lightness, red/green intensity, and yellow/blue intensity, as L*, a*, and b* values, respectively. Additionally, skin color's full spectral characteristics and cutaneous physiology can be measured with spectrophotometers. This article outlines basic principles of the CIELAB color system and how to optimally use colorimetric devices as a skin research tool.

Analysis of facial redness by comparing VISIA® from Canfield and CSKIN® from Yanyun Technology

“…The calibrated CIE 1976 ( L*a*b* ) color space, or CIELAB, which is commonly used as an absolute color scale for analysis of skin erythema, 21 serves as a device‐independent model. The a* value was reported by Yun and Ly et al showing a positive correlation with the erythema 19,22 . Reported by Taylor et al, a CIELAB‐based color display necessarily conveys to a viewer more and more accurate information about two grayscale images than any RGB color space‐based display 23 .…”

“…The assessment of skin color is of the utmost importance for dermatological clinicians. The human eye, known to have a high power of discrimination between colors including shades (luminance) and hues (reflection of specific wavelengths of light), 18,19 is the first diagnostic tool for the dermatologists. However, the evaluation and perception of skin color with eyes are limited by assorted influential factors such as age, hereditary, and disease, 15 which often leads to unreliable results.…”

Improved HPLC Conditions to Determine Eumelanin and Pheomelanin Contents in Biological Samples Using an Ion Pair Reagent

“…Correlations of PTCA, TTCA and 4-AHP to Individual Typology Angle (ITA), a measure of objective color assessment [ 23 , 24 ], are presented in Figure S2 . Except for 4-AHP (R 2 = 0.355), PTCA (R 2 = 0.920) and TTCA (R 2 = 0.913) values showed good correlations with ITA values.…”

“…Units for the y -axis are µg/mg. Actual ITA values (greater and positive values for paler skin and smaller and negative values for darker skin) [ 8 , 23 , 24 ] are converted to positive values by values being reversed and the y -axis being moved to the left end [ 8 ]. Correlation formulae are based on actual values of ITA.…”

A Face Detection Method Based on Skin Color Model and Improved AdaBoost Algorithm

“…It often mistakes areas with skin color or skin-like color for faces. Moreover, this approach is severely affected by light [4]. The AdaBoost-based face detection method boasts a high detection rate and a low false detection rate for images of frontal faces in simple backgrounds.…”