• The Journal of Advanced Prosthodontics
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• v.10 no.6
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• pp.422-429
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• 2018

PURPOSE. Accurate color matching of maxillofacial prostheses to skin is important for esthetics. A computerized color matching system specific to human skin has recently been developed. The purpose of this study was to evaluate the accuracy in color and translucency matching of the computerized color matching system across different skin colors. MATERIALS AND METHODS. The silicone was colored to simulate 28 different skin colors (n=5) to serve as "target skin colors". Using a spectrocolorometer (e-skin), color codes were determined for "replicate skin color" fabrication. CIELAB Delta-E between target skin color-replicate skin color pairs and translucency parameter were calculated. CIELAB Delta-E values were compared with one-way ANOVA and Tukey multiple-comparison. The agreement between $L^*$, $a^*$, $b^*$ and translucency parameter of target skin colors and replicate skin color were calculated by a two-way mixed average measures intraclass correlation coefficient. Translucency parameter of target skin color- replicate skin color pairs were compared with Paired t-test (${\alpha}=.05$). RESULTS. The mean CIELAB Delta-E value was 3.83 and significant differences were found among colors. The intraclass correlation coefficient showed excellent reliability for $L^*$, $a^*$, $b^*$ and good reliability for translucency parameter (P<.001). The mean translucency parameter of replicate skin colors was significantly higher than that of translucency parameter. CONCLUSION. The computerized color matching system specific to human skin was found to be reliable in terms of color and translucency between target skin colors and replicate skin color.

• Journal of Korean Ophthalmic Optics Society
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• v.8 no.1
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• pp.53-57
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• 2003

R, G, Y, B color lenses Manufactured increasing tinted time by 5 min term. CIE $L^*a^*b^*$ coordination's analysis used spectrophotometer and CIE $L^*a^*b^*$ color system. CIE $L^*a^*b^*$ coordination transfer form about tinted time being $$b^*(Y-B)={\beta}a^*+{\alpha}$$ change to do linear almost. In red case, move in $G{\rightarrow}R$, $B{\rightarrow}Y$ form tinted time increases, and Parameter ${\alpha}$, ${\beta}$ value got each -3.49 and 0.90. In green case, CIE $L^*a^*b^*$ coordination transfer form is $R{\rightarrow}G$, $B{\rightarrow}Y$ form. Got the pure green color color in 10 min's tinted time. Parameter ${\alpha}$, ${\beta}$ value got each -0.72 and -0.55. Get into pure yellow and blue color case tinted time increases. Parameter ${\alpha}$, ${\beta}$ value are 14.11 and 1.58 in yellow, and Parameter ${\alpha}$, ${\beta}$ value are -11.62 and 1.30 in blue color.

• Journal of the Optical Society of Korea
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• v.18 no.2
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• pp.184-187
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• 2014

This study examined the effects of particle size on the light scattering of a nano-sized color filter pigment used to obtain a range of colors in liquid crystal displays. The contrast ratio is one of the most important characteristics of liquid crystal displays. When a color filter is located between two crossed polarizers, the size of the pigment can give rise to a decrease in the contrast ratio due to Rayleigh scattering by the nanoparticles in the filter. The size effect of the color filter pigment on the contrast ratio was investigated in terms of the depolarization parameter. As an experimental result, the depolarization parameter increased with decreasing pigment size. Therefore, a smaller pigment size can reduce light leakage caused by light scattering in the color filter between two crossed polarizers. The depolarization function was also proposed as a useful function for predicting the decrease in the contrast ratio of the color filter.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1048-1052
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• 2004

In this work, we have investigated a role of linking parameter in Pulse-Coupled Neural Network(PCNN) which is suggested to explain the synchronous activities among neurons in the cat cortex. Then we have found a method to determine the linking parameter for a satisfactory face detection performance in a given color image. Face detection algorithm which uses the color information is independent on pose, size and obstruction of a face. But the use of color information encounters some problems arising from skin-tone color in the background, intensity variation within faces, and presence of random noise and so on. Depending on these conditions, PCNN's linking parameters should be selected an appropriate values. First we obtained the mean and variance of the skin-tone colors by experiments. Then, we introduced a preprocess that the pixel with a mean value of skin-tone colors has the highest level value (255) and the other pixels have values between 0 and 255 according to normal distribution with a variance. This preprocessing leads to an easy decision of the linking parameter of the Pulse-Coupled Neural Network. Through experiments, it is verified that the proposed method can improve the face detection performance compared to the existing methods.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.32-42
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• 2017

This paper proposes a new haze removal method for moving image sequence. Since the conventional dark channel prior haze removal method adjusts each color component separately in RGB color space, there can be severe color distortion in the haze removed output image. In order to resolve this problem, this paper proposes a new haze removal scheme that adjusts luminance and saturation components in HLS color space while retaining hue component. Also the conventional dark channel prior haze removal method is developed to obtain best haze removal performance for a single image. Therefore, if it is applied to a moving image sequence, the estimated parameter values change rapidly and the haze removed output image sequence shows unnatural glitter defects. To overcome this problem, a new parameter estimation method using Kalman filter is proposed for moving image sequence. Experimental results demonstrate that the haze removal performance of the proposed method is better than that of the conventional dark channel prior method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.132-145
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• 2009

We present the framework for JND based Illumination and Color Restoration Using Edge-preserving filter for restoring distorted images taken under the arbitrary lighting conditions. The proposed method is effective for appropriate illumination compensation, vivid color restoration, artifacts suppression, automatic parameter estimation, and low computation cost for HW implementation. We show the efficiency of the mean shift filter and sigma filter for illumination compensation with small spread parameter while considering the processing time and removing the artifacts such as HALO and noise amplification. The suggested CRF (color restoration filter) can restore the natural color and correct color distortion artifact more perceptually compared with current solutions. For the automatic processing, the image statistics analysis finds suitable parameter using JND and all constants are pre-defined. We also introduce the ROI-based parameter estimation dealing with small shadow area against spacious well-exposed background in an image for the touch-screen camera. The object evaluation is performed by CMC, CIEde2000, PSNR, SSIM, and 3D CIELAB gamut with state-of-the-art research and existing commercial solutions.

• Korean Journal of Mathematics
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• v.29 no.2
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• pp.271-291
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• 2021

Hom-Lie-Yamaguti color algebras are defined and their representation and cohomology theory is considered. The (2, 3)-cocycles of a given Hom-Lie-Yamaguti color algebra T are shown to be very useful in a study of its deformations. In particular, it is shown that any (2, 3)-cocycle of T gives rise to a Hom-Lie-Yamaguti color structure on T⊕V , where V is a T-module, and that a one-parameter infinitesimal deformation of T is equivalent to that a (2, 3)-cocycle of T (with coefficients in the adjoint representation) defines a Hom-Lie-Yamaguti color algebra of deformation type.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.569-572
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• 1999

In this paper we present a color image segmentation algorithm based on statistical models. A novel deterministic annealing Expectation Maximization(EM) formula is derived to estimate the parameters of the Gaussian Mixture Model(GMM) which represents the multi-colored objects statistically. The experimental results show that the proposed deterministic annealing EM is a global optimal solution for the ML parameter estimation and the image field is segmented efficiently by using the parameter estimates.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.401-404
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• 2006

Mean shift procedure is applied for the data points in the joint spatial-range domain and achieves a high quality. However, a color image is segmented differently according to the inputted spatial parameter or range parameter and the demerit is that the image is broken into many small regions in case of the small parameter. In this paper, to improve this demerit, we propose the method that groups similar regions using region merging method for over-segmented images. The proposed method converts a over-segmented image in RGB color space into in HSI color space and merges similar regions by hue information. Here, to preserve edge information, the proposed method use by merging constraints to decide whether regions is merged or not. After then, we merge the regions in RGB color space for non-processed regions in HSI color space. Experimental results show the superiority in region's segmentation results.

• The Journal of the Korea Contents Association
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• v.6 no.9
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• pp.19-27
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• 2006

Mean shift procedure is applied for the data points in the joint spatial-range domain and achieves a high quality. However, a color image is segmented differently according to the inputted spatial parameter or range parameter and the demerit is that the image is broken into many small regions in case of the small parameter. In this paper, to improve this demerit, we propose the method that groups similar regions using region merging method for over-segmented images. The proposed method converts a over-segmented image in RGB color space into in HSI color space and merges similar regions by hue information. Here, to preserve edge information, the region merge constraints are used to decide whether regions are merged or not. After then, we merge the regions in RGB color space for non-processed regions in HSI color space. Experimental results show the superiority in region's segmentation results.