• Journal of the Korean Wood Science and Technology
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• v.33 no.4 s.132
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• pp.23-29
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• 2005

The fancy veneer flooring board is high value-added wooden material. The classification of the flooring boards by the observation with the naked eye causes color difference among fancy veneers. It turned out that this inaccuracy of color difference among fancy veneers increased in case of the identification by metamerism or the flooring construction. Therefore, this study was performed to classify fancy veneers produced from 3 species such as Tilia sp., Betula sp., and Acer sp. which were identified with the naked eye by Light and Dark grade, by using CIELAB. In addition, each specie's threshold on CIERGB was investigated and a range of hue, saturation and intensity by an application of HSI color model were studied. Intensity of the HIS color model could be the best value to be used when color, saturation and intensity of the HSI color model were used for the classification of the flooring board's color. In addition, it seemed that color range of all three criteria lied between $45^{\circ}$ and $55^{\circ}$. In the case of identification by threshold of RGB element, considering only specific color element value is unlikely to lead to accurate classification of fancy veneers of flooring board.

• Journal of Technologic Dentistry
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• v.39 no.4
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• pp.227-233
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• 2017

Purpose: The purpose of this study was to evaluate the validity of digital models fabricated by difference optical source of non-contact 3D dental scanner. Methods: A master model with the prepared upper full arch tooth was used. Stone model(N=10) were produced from master model, and on the other hands, digital models were made with the 3D dental scanner(Blue, white, red optical source). The linear distance between the reference points were measured and analyzed on the Delcam $Copycad^{(R)}$ graphic software. The results were statistically analyzed using the one-way ANOVA and Tukey's HSD test(${\alpha}=0.05$). Results: There were considerable differences in mean values between optical source within each color(blue, white, red), and this difference was not statistically significant(p>0.05). Conclusion : Three different color of dental scanner optical source showed clinically acceptable accuracies of full arch digital model produced by them. Besides, these results will have to be confirmed in further clinical studies.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.65-84
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• 2006

In this paper, we present an improved image formation model and propose a color image enhancement based on the model. In the presented image formation model, an input image is represented as a product of global illumination, local illumination, and reflectance. In the proposed color image enhancement, an input RGB color image is converted into an HSV color image. Under the assumption of white-light illumination, the H and S component images are remained as they are and the V component image only is enhanced based on the image formation model. The global illumination is estimated by applying a linear LPF with wide support region to the input V component image and the local illumination by applying a JND (just noticeable difference)-based nonlinear LPF with narrow support region to the processed image, where the estimated global illumination is eliminated from the input V component image. The reflectance is estimated by dividing the input V component image by the estimated global and local illuminations. After performing the gamma correction on the three estimated components, the output V component image is obtained from their product. Histogram modeling is next executed such that the final output V component image is obtained. Finally an output RGB color image is obtained from the H and S component images of the input color image and the final output V component image. Experimental results for the test image DB built with color images downloaded from NASA homepage and MPEG-7 CCD color images show that the proposed method gives output color images of very well-increased global and local contrast without halo effect and color shift.

• Journal of Technologic Dentistry
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• v.34 no.4
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• pp.369-377
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• 2012

Purpose: The aim of study was to compare the dimensional stability of digitized dental stone replica using different color of gypsum materials using a white light scanner with three-dimensional software. Methods: A master model(500B-1, Nissin dental product, Japan) with the prepared lower full arch tooth was used. Several type IV stones(white, yellow, green) were used for 30 stone casts(10 casts each) duplicated a master model of mandible. The master model and the replicas were digitized with the non-contacting white light scanner to create 3-dimensional digital models. The linear distance between the reference points were measured and analyzed on the Delcam Copycad$^{(R)}$(Delcam plc, UK) 3D graphic software. One-way analysis of variance(ANOVA) combined with a Tukey multiple-range test were used to analysis the data(${\alpha}$=0.05). Results: There were considerable differences in mean values between gypsum materials within each color(white, yellow, green), and this difference was statistically significant, p=0.001. Conclusion: Digitization of dental materials on optical scanner was affected by color. Three different color of gypsum materials showed clinically acceptable accuracies of full arch digital model produced by them. Besides, these results will have to be confirmed in further clinical studies.

• Journal of KIISE
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• v.42 no.10
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• pp.1294-1302
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• 2015

A lot of image quality assessment metrics that can precisely reflect the human visual system (HVS) have previously been researched. The Structural SIMilarity (SSIM) index is a remarkable HVS-aware metric that utilizes structural information, since the HVS is sensitive to the overall structure of an image. However, SSIM fails to deal with color difference in terms of the HVS. In order to solve this problem, the Structural and Hue SIMilarity (SHSIM) index has been selected with the Hue, Saturation, Intensity (HSI) model as a color space, but it cannot reflect the HVS-aware color difference between two color images. In this paper, we propose a new image quality assessment method for a color image by using a CIE Lab color space. In addition, by using a support vector machine (SVM) classifier, we also propose an optimization system for applying optimal metric according to the types of distortion. To evaluate the proposed index, a LIVE database, which is the most well-known in the area of image quality assessment, is employed and four criteria are used. Experimental results show that the proposed index is more consistent with the other methods.

• Restorative Dentistry and Endodontics
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• v.34 no.3
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• pp.199-207
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• 2009

The objective of this study was to evaluate the effect of color measuring instrument by measuring the color of dental composite resins. Nine shade light cured composite resin disks were prepared (diameter : 15 mm, thickness : 4 mm). CIE $L^*a^*b^*$ color scale of each disk was measured with 3 different types of spectrophotometer [MiniScan XE plus (Model 4000S, Hunter Lab, USA), CM-3500d (Minolta, Japan) and Specbos 2100 Miniature VIS Reflection spectrometer (Serial No: 319416, JETI Technishe VIS Instrumentic GmbH. Germany)]. Miniscan XE Plus and CM-3500d using identical measuring geometry with different size of viewing aperture. But Specbos 2100 using different measuring geometry. Within the limitation of this study, there were color difference (${\Delta}E^*$) from 2.4 to 7.8 between Miniscan XE Plus and CM-3500d, but $L^*$, $a^*$, $b^*$ values showed the high correlation. However, there were great color difference (${\Delta}E^*$) in the extent of about 20 between instruments with the different measuring geometry. Therefore, color scale measured by color measuring instrument should be used as a relative value rather than an absolute value in the field of dentistry.

• Restorative Dentistry and Endodontics
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• v.46 no.4
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• pp.47.1-47.9
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• 2021

Objectives: This study aimed to use a laboratory model to evaluate the efficacy of an experimental bleaching agent. Materials and Methods: The model used human extracted molars that were treated and measured for bleaching efficacy. Teeth (n = 50) were distributed into 5 groups: Negative control (NC): immersion in water for 8 hours; Nanofibers (NFs): Experimental titanium dioxide nanofibers with stirring and light activation for 8 hours; Whitestrips (WS): Crest 3D White Glamorous White Whitestrips, 2 applications daily for 30 minutes, 14 days; 1% hydrogen peroxide (HP) standard: 1% hydrogen peroxide for 8 hours; and 30% HP standard: 30% hydrogen peroxide for 8 hours. Instrumental measurements were performed using a spectrophotometer. Results were recorded at baseline, 1-day post-bleaching, and 1-week post-bleaching. Kruskal-Wallis procedure was used to determine differences in color change. Pearson correlation was used to evaluate the relationship between visual and instrumental measurements. Tests of hypotheses were 2-sided with alpha = 0.05. Results: There was no significant difference in color parameters (L1, a1, b1, and shade guide units [SGU]) at baseline (p > 0.05). There was a significant difference among the groups for overall color change (ΔE^*ab) and change in shade guide units (ΔSGU) at 1-day and 1-week post-bleaching (p < 0.05). The higher the HP concentration, the higher the color change as expressed in ΔSGU and ΔE^*ab. The negative control exceeded the perceptibility threshold of ΔE^* = 1.2 regardless of time point. NFs showed a decrease in chroma, but were not statistically different compared to the negative control. Conclusions: The laboratory model was successful in screening an experimental bleaching agent.

• Preventive Nutrition and Food Science
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• v.13 no.4
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• pp.306-312
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• 2008

This study investigated the influence of pH on the color development of melanoidins formed from amino acid enantiomer model systems. For this, the color development was evaluated by measuring browning at 420 nm and color measurements by spectrophotometry and colorimetry. The browning and browning index showed no difference according to the type of amino acid enantiomers, while that formed from the D-Asn system was the only difference according to pH level. The tristimulus value of melanoidins formed from all model systems was located on a dominant wavelength of 475 nm, the blue zone of the diagram. In addition, the $L^*$, $a^*$, $b^*$, $C^*_{ab}$ values, and ${\Delta}E^*$ index on the basis of the type of amino acid enantiomers, the differences were markedly found at pH 4.0. At pH 7.0, significantly differences were found in the $L^*$, $a^*$, $b^*$ values, and ${\Delta}E^*$ index and not in the case of the lysine enantiomers. In addition, at pH 10.0, the differences were found in the $a^*$ and $b^*$ values from the lysine enantiomers and $C^*_{ab}$ value from the asparagine enantiomers. Therefore, the color development of melanoidins was influenced by the type of amino acid enantiomers and pH levels. Especially, it is thought that the $a^*$ and $b^*$ values can be used to explain the differences among the amino acid enantiomers in the color development of melanoidins.

• Journal of the Korean Institute of Educational Facilities
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• v.20 no.3
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• pp.29-39
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• 2013

This study addresses the evaluation on the satisfaction of school illumination quality by applying SERVPERF model after extracting factors affecting school illumination quality. Three types of illumination systems (fluorescence light, general LED light and high color rendition LED light) were tested by students who have used each illumination system. Three factors such as effectiveness, esthetic sense and function were developed for evaluation. Satisfaction evaluation was performed based on applied SERVPERF model by comparing perceived levels. The differences of perceived levels of satisfaction on the illumination systems were analyzed by ANOVA. The results said respondents satisfy only the high color rendition LED light regardless of three factors. Especially, students who experienced high color rendition LED light have strong intention to recommend that illumination system to other schools. They also express their desire to use that system at home. Interestingly, there is not much satisfaction difference between fluorescence light and general LED light.

• Journal of Biosystems Engineering
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• v.17 no.4
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• pp.382-395
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• 1992

The surface color of several varieties of apples were expressed quantitatively in xyz chromaticity coordinates. The spectral reflectance of 'Fuji' apples were measured in 400-820 nm range by using a spectrophotometer. Based on the spectrophotometer data and the result of visual sensory test, linear regression models were developed to select wavelengths effective for sorting apples. The models utilized reflectance at single wavelength, and the difference and ratio of the reflectance at two distinct wavelengths. The model which best fitted the visual sensory test data was one utilizing the ratio of the reflectance at 618 nm and 514nm. The correlation coefficient for this model was 0.967. Several other models were also described.