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Spectral Reflectance of Skin Color and Its Applications to Color Appearance Modeling

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Spectral Reflectance of Skin Color and Its Applications to Color Appearance Modeling Spectral Reflectance of Skin Color and its Applications to Color Appearance Modeling Francisco Hideki Imai, Norimichi Tsumura, Hideaki Haneishi and Yoichi Miyake Department of Information and Computer Sciences, Chiba University, Chiba, Japan Abstract experiments based on the memory matching method. The difference of appearance between skin color patch and fa- Fifty-four spectral reflectances of skin colors (facial pat- cial pattern is also discussed and analyzed. tern of Japanese women) were measured and analyzed by the principal component analysis. The results indicate that Principal Component Analysis of Spectral the reflectance spectra can be estimated approximately 99% Reflectance of Human Skin by only three principal components. Based on the experi- mental results, it is shown that the spectral reflectance of Ojima et al.1 measured one hundred eight spectral all pixels in skin can be calculated from the R, G, B signals reflectances of skin in human face for 54 Mongolians (Japa- of HDTV (High Definition Television) camera. nese women) who are between 20 and 50 years old. The Computer simulations of color reproduction in skin spectral reflectance was measured at intervals of 5 nm be- color have been developed in both colorimetric color re- tween 400 nm and 700 nm. Therefore, the spectral reflec- production and color appearance models by von Kries, LAB tance is described as vectors o in 61-dimensional vector and Fairchild. The obtained color reproduction in facial pat- space. The covariance matrix of the spectral reflectance tern and skin color patch under different illuminants are was calculated for the principal component analysis. Then, analyzed. Those reproduced color images were compared the spectral reflectance of human skin can be expressed as by memory matching method. The difference of appear- a linear combination of the principle component vectors as ance models is described and the difference of appearance follows: between skin color patch and facial pattern is also discussed 61 and analyzed. = + α o o ∑ iui , (1) i=1 Introduction where o is the averaged spectral reflectance, ui (i = 1...61) α In desktop publishing of digital photography, cross-media are the eigenvectors and i (i = 1...61) are the eigenvalues. corresponding color reproduction of portrait under various The eigenvectors are combined in order of the eigenvalues. illuminants is desirable. To achieve color appearance The cumulative proportion ratio of these principle com- matches across media, the traditional colorimetric method ponents shows that the spectral reflectance of human skin must be enhanced using color appearance models. can be represented approximately 99.5% by using linear A previous work shows that the spectral reflectance of combination of three principal components.1 Therefore the human skin can be represented by three basis functions Equation (1) can be represented approximately as follows: based on the principal component analysis.1 Then, the two α dimensional distribution of spectral reflectance of the skin 3 1 can be estimated using the values of three color channels ≅ + α = + ( )α o o ∑ iui , o u1 u2 u3 2 (2) and the spectral radiance of the illuminant, as is performed i=1 α in electronic endoscope images.2 The colorimetric color re- 3 production under various illuminants3 can be achieved us- ing both the estimated spectral reflectance of the object and Colorimetric Color Reproduction of Skin the spectral radiance of the illuminant. In this paper, we propose a color reproduction method Figure 1 shows schematic diagram of color reproduction to predict the appearance of skin color image under vari- from an image taken by HDTV camera to CRT or hardcopy ous viewing illuminants4 using the colorimetric informa- of skin color under various illuminants. A skin color image tion of skin color images taken by HDTV camera. In this taken by HDTV camera was transformed from the original method chromatic adaptation transformations proposed by RGB data to X, Y, and Z tristimulus values by matrix M1 von Kries5 and Fairchild6, and LAB7 color space is applied obtained by multiple regression analysis of skin color patch. to the colorimetric color reproduction obtained by princi- A two dimensional distribution of spectral reflectances of pal components of human skin reflectance.3 By this method skin O(i, j,λ), where i, j are the coordinates of the image, is we can achieve the corresponding color reproduction on a estimated using three principal components of the reflec- CRT display of printed skin color images under various tance of the skin. The tristimulus values X', Y', Z' of skin viewing illuminants. Optimum color appearance model to color under a selected illuminant are easily calculated from predict color reproduction is selected by psychophysical O(i, j,λ) and the spectral radiance E(λ) of the illuminant. 130—Recent Progress in Color Processing The predicted tristimulus values are displayed on CRT and dicted color reproduction for skin color patches and facial printed by color transform matrix for calibration. Then, the images in the viewing booth were displayed on CRT. Three skin color image is reproduced colorimetrically both on images, predicted using von Kries, Fairchild, CIELAB CRT display and hardcopy. models, and XYZ image without considering chromatic adaptation were calculated for each viewing illuminant. Corresponding Color Reproduction A memory matching method, recommended by Braun of Skin Color and Fairchild,8 was used to select an optimum color ap- pearance model for skin color images displayed on a CRT. Figure 2 shows a schematic diagram of the proposed cor- The CRT display and the standard illumination booth were responding color reproduction method for skin color. By angularly positioned at 90° such that the observers can only using color appearance models, the tristimulus values Xa, see one of them at a time. Ya, and Za after the chromatic adaptation can be calculated Ten observers (students involved in image processing) from the tristimulus values X’, Y’, and Z’ obtained by colo- viewed the images in the illumination booth for a minute rimetric color reproduction. The first step is a transforma- to stabilize the perception of the color. Then, they would tion from tristimulus values, X’, Y’, and Z’ to cone funda- view the CRT display where four predicted images, XYZ, mental tristimulus values L, M, and S using the Hunt- von Kries, Fairchild, CIELAB images are displayed. Ob- Pointer-Estévez transformation normalized to CIE servers were instructed to choose the best prediction in the Illuminant D65. The values La , Ma , and Sa which are the four images on CRT display. The psychophysical experi- cone responses after the chromatic adaptation were pre- ment was performed for both skin color patch and facial dicted from the L, M, S values using von Kries, LAB, and images. Fairchild models. Then, the tristimulus values Xa, Ya, and Za, considering chromatic adaptation, are calculated by the Experimental Results and Discussion inverse of matrix M2. Finally, the predicted image with tristimulus values Xa, Ya, and Za is reproduced on CRT dis- Figure 3(a) shows the percentage of trials for which each play by color transform matrix. reproduced model on CRT display was selected as the most similar color reproduction to an hardcopy illuminated by Psychophysical Experiment to Select an various illuminants. As a result, in an average of 68% of Optimum Color Appearance Model the trials the observers selected Fairchild model. Figure 3(b) for Proposed Method shows the percentage of trials for the selected color repro- duction on CRT as the most similar one to an hardcopy Color appearance models to predict color reproduction was illuminated by each illuminant in the booth. We can see estimated by psychophysical experiments. The images on that the incomplete adaptation proposed by Fairchild, was CRT display surrounded by a dark environment were com- effective under “Cool White”, “Horizon”, and Illuminant pared with a hardcopy illuminated in the standard illumi- “A”. However, under “Day Light” the Fairchild model was nation booth (Macbeth Spectralight II). The booth has four not as effective as other illuminants, because under this illuminants; “Day light” (CIE D65), “A” (2,856 K), “Cool illuminant there is no significant degree of adaptation, and white” (4,150 K), and “Horizon” (2,300 K). there is no perceptible differences between the images pre- Five facial images of a Japanese young women were dicted by von Kries and Fairchild models. taken by a HDTV camera and digitized with 8 bits to get an On the other hand, Figure 4(a) shows the percentage image of 1920 by 1035 pixels. Six skin color patches with of selected facial pattern image reproductions on CRT ac- same color in facial pattern are also prepared. The pre- cording to the criterion of similarity to a hardcopy under HDTV ( X', Y' Z' ) Three principal components , of spectral reflectance of skin Color transform matrices O ( i, j, λ ) ( R, G, B ) M E(λ ) 1 ( X, Y, Z ) CRT display Hardcopy Figure 1. Diagram of colorimetric color reproduction of skin color image under various illuminants. Chapter I—Color Appearance—131 ( X, Y, Z ) M 2 -1 M2 Three principal components (L, M, S ) (X , Y , Z ) of spectral reflectance of skin a a a Color Transform Matrix O(i, j, λ) Color appearance E(λ ) models (( X', Y', Z' ) (La, Ma, Sa ) CRT display Figure 2. Diagram of corresponding color reproduction of skin color image under various illuminants. 100 100 90 Patch 1 90 80 80 70 Patch 2 70 Illuminant "A" 60 Patch 3 60 "Day light" 50 50 Patch 4 "Horizon" 40 40 30 Patch 5 30 "Cool White" Percentage chosen Percentage chosen 20 Patch 6 20 10 10 0 0 XYZ CIELAB von Kries Fairchild XYZCIELAB von Kries Fairchild (a) Selected model in the prediction of the color appearance (b) Selected model in the prediction of the color appearance for each skin color patch under various illuminants.
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