Measurement of melanin concentration, blood concentration and oxygen saturation in skin tissue is highly important technology in medical and cosmetic fields. Most previous studies neglect depth inhomogeneity of blood concentration distribution in skin tissue. However, skin tissue has a complex layered structure, and it is known that distribution of blood concentration differs greatly depending on the depth. Although a method has been proposed considering the inhomogeneity of blood distribution in depth direction, it is impossible to measure oxygen saturation. In addition, there is a limitation that shading influences the estimation as noise in any of the methods. Therefore, in this study, we propose a method to measure skin components concentration, which are melanin concentration, blood concentration, and oxygen saturation, in layers with different depths of skin tissue without influence of shading. First, to construct a dataset of absorbance corresponding to the skin components concentration we construct an optical multi-layered model of skin tissue and simulate light propagation and attenuation by light scattering and absorption with Monte Carlo simulation method. Each absorbance value is converted to a relative value based on an averaged absorbance value of all wavelengths to remove influence of shading. Next, we create a model describing an absorbance value corresponding to the skin components concentration with high dimensional multivariate regression based on the created dataset. This model enables to estimate the skin components concentration from spectral information without influence of shading. The proposed method is evaluated by simulation and shown to have state-of-the-art performance.
This paper proposes to apply nonlinear estimation of chromophore concentrations: melanin, oxy-hemoglobin, deoxyhemoglobin and shading to the real hyperspectral image of skin. Skin reflectance is captured in the wavelengths between 400nm and 700nm by hyperspectral scanner. Five-band wavelengths data are selected from skin reflectance. By using the cubic function which obtained by Monte Carlo simulation of light transport in multi-layered tissue, chromophore concentrations and shading are determined by minimize residual sum of squares of reflectance. When dark circles are appeared under the eyes, the subject looks tired and older. Therefore, woman apply cosmetic cares to remove dark circles. It is not clear about the relationship between color and chromophores distribution in the dark circles. Here, we applied the separation method of the skin four components to hyperspectral image of dark circle, and the separated components are modulated and synthesized. The synthesized images are evaluated to know which components are contributed into the appearance of dark circles. Result of the evaluation shows that the cause of dark circles for the one subject was mainly melanin pigmentation.
In this paper, principal component analysis is applied to pigmentation distributions, surface reflectance components and
facial landmarks in the whole facial images to obtain feature values. Furthermore, the relationship between the obtained
feature vectors and age is estimated by multiple regression analysis to modulate facial images in woman of ages 10 to 70.
In our previous work, we analyzed only pigmentation distributions and the reproduced images looked younger than the
reproduced age by the subjective evaluation. We considered that this happened because we did not modulate the facial
structures and detailed surfaces such as wrinkles. By analyzing landmarks represented facial structures and surface
reflectance components, we analyzed the variation of facial structures and fine asperity distributions as well as
pigmentation distributions in the whole face. As a result, our method modulate the appearance of a face by changing age
more appropriately.
To quantitatively evaluate skin chromophores over a wide region of curved skin surface, we propose an approach that suppresses the effect of the shading-derived error in the reflectance on the estimation of chromophore concentrations, without sacrificing the accuracy of that estimation. In our method, we use multiple regression analysis, assuming the absorbance spectrum as the response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as the predictor variables. The concentrations of melanin and total hemoglobin are determined from the multiple regression coefficients using compensation formulae (CF) based on the diffuse reflectance spectra derived from a Monte Carlo simulation. To suppress the shading-derived error, we investigated three different combinations of multiple regression coefficients for the CF. In vivo measurements with the forearm skin demonstrated that the proposed approach can reduce the estimation errors that are due to shading-derived errors in the reflectance. With the best combination of multiple regression coefficients, we estimated that the ratio of the error to the chromophore concentrations is about 10%. The proposed method does not require any measurements or assumptions about the shape of the subjects; this is an advantage over other studies related to the reduction of shading-derived errors.
We adapted the critical angle method for measuring rough surfaces under partial contact to acquire an in vivo skin refractive index (RI). Assuming that the total reflection is the simple sum of reflection from areas that are in contact and reflection from those that are not in contact, the RI can be estimated even for partial contact with a rough surface. We found that cheek skin is sufficiently soft that a sufficiently large area can be in contact and that the critical angle was detectable. The RIs of the cheeks of adult females were measured. The RI range was about 1.51 to 1.53, at a wavelength of 550 nm, without considering systematic errors. The RIs of cheeks are significantly correlated with their conductance, which corresponds to their water content. We determined the relationship between the RI and conductance within the variation of skin under normal conditions; this relationship was theoretically obtained in previous studies. In the present study, a direct in vivo measurement method was developed that enabled us to measure the RI in daily life, although this method contains errors for several reasons, including disregarding
We have developed a simple and effective method for everyday measurement of translucency with a handy spectral reflectometer using edge loss. Edge loss can be used to quantify the translucency index in terms of changes in reflectance under two types of measurement conditions. Here, a measurement condition represents the pairing of an illumination area and a measurement area. As a measure of the degree of lateral spread of reflected light, the translucency index can influence the appearance of human skin because this index represents eventual translucency. First, we estimated how edge loss changes when measurement conditions are varied. We then selected the combination of two measurement conditions of large and small edge loss to minimize errors. Finally, we estimated actual skin translucency changes before and after treatments comprising acetone-ether immersion and ultraviolet irradiation. The results were qualitatively consistent with the expectations under variations in absorbance and scattering capacity, indicating the effectiveness of this method in evaluating translucency. This method allows simultaneous measurement of translucency and reflectance as a spectrum, and also appears applicable for daily use, although common optical parameters cannot be derived using this method alone.
Uneven distribution of skin color is one of the biggest concerns about facial skin appearance. Recently several
techniques to analyze skin color have been introduced by separating skin color information into chromophore
components, such as melanin and hemoglobin. However, there are not many reports on quantitative analysis of
unevenness of skin color by considering type of chromophore, clusters of different sizes and concentration of the each
chromophore. We propose a new image analysis and simulation method based on chromophore analysis and spatial
frequency analysis. This method is mainly composed of three techniques: independent component analysis (ICA) to
extract hemoglobin and melanin chromophores from a single skin color image, an image pyramid technique which
decomposes each chromophore into multi-resolution images, which can be used for identifying different sizes of
clusters or spatial frequencies, and analysis of the histogram obtained from each multi-resolution image to extract
unevenness parameters. As the application of the method, we also introduce an image processing technique to change
unevenness of melanin component. As the result, the method showed high capabilities to analyze unevenness of each
skin chromophore: 1) Vague unevenness on skin could be discriminated from noticeable pigmentation such as freckles
or acne. 2) By analyzing the unevenness parameters obtained from each multi-resolution image for Japanese ladies, agerelated
changes were observed in the parameters of middle spatial frequency. 3) An image processing system
modulating the parameters was proposed to change unevenness of skin images along the axis of the obtained age-related
change in real time.
In the cosmetics industry, skin color is very important because skin color gives a direct impression of the face. In particular, many people suffer from melanin pigmentation such as liver spots and freckles. However, it is very difficult to evaluate melanin pigmentation using conventional colorimetric values because these values contain information on various skin chromophores simultaneously. Therefore, it is necessary to extract information of the chromophore of individual skins independently as density information. The isolation of the melanin component image based on independent component analysis (ICA) from a single skin image was reported in 2003. However, this technique has not developed a quantification method for melanin pigmentation. This paper introduces a quantification method based on the ICA of a skin color image to isolate melanin pigmentation. The image acquisition system we used consists of commercially available equipment such as digital cameras and lighting sources with polarized light. The images taken were analyzed using ICA to extract the melanin component images, and Laplacian of Gaussian (LOG) filter was applied to extract the pigmented area. As a result, for skin images including those showing melanin pigmentation and acne, the method worked well. Finally, the total amount of extracted area had a strong correspondence to the subjective rating values for the appearance of pigmentation. Further analysis is needed to recognize the appearance of pigmentation concerning the size of the pigmented area and its spatial gradation.
Skin color reproduction becomes increasingly important with the recent progress in various imaging systems. In this paper, based on subjective experiments, correlation maps are analyzed between appearance of Japanese facial images and amount of melanin and hemoglobin components in the facial skin. Facial color images were taken by digital still camera. The spatial distributions of melanin and hemoglobin components in the facial color image were separated by independent component analysis of skin colors. The separated components were synthesized to simulate the various facial color images by changing the quantities of the two separated pigments. The synthesized images were evaluated subjectively by comparing with the original facial images. From the analysis of correlation map, we could find the visual or psychological terms that are well related to melanin components influence the appearance of facial color image.
We are developing a spectral characteristics database for evaluating color reproduction in image input devices. The database is designed so that spectral characteristics are systematically divided by category, according to the purpose to which they are to be applied, and every category has a sufficient variety of samples. The categories are as follows: photographic materials, graphic color printing, computer color printers output, paints, flowers, leaves, human skin colors and historical Krinov data. The total number of colors is 49,672. The database is being proposed to be published as Japanese/International standard technical reports for use in establishing a new color reproduction evaluation method.
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