• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.261-265
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• 2002

The unique colors of paper, that is, blue, green, red, and yellow were used in the estimation of color from the subjective feeling. The monochrome with unique color or the unique color surrounded with the background color was presented. Subject gazed the monochrome or the unique color, which was called target color. The target and background color were the complementary color each other. The various ratios of the area of gazed color and background were taken. Subject answered the level of subjective feeling consisted of pair of adjective items for unique color presented. With the use of the subjective feeling fer the target color presented, the estimation of the unique color was carried out due to Fuzzy theory and neural networks. The results of color difference between unique color presented and the estimated color gave very small value for the case without background, while the results of the case with background color depended on the ratio of area of presented color and background color till the ration of 2:1, The relation showed the Kirschman's law. The color difference saturated in the increase of area of background with the ratio more than 2:1.

• Science of Emotion and Sensibility
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• v.5 no.2
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• pp.73-78
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• 2002

The unique colors of paper, that is, blue, green, red, and yellow were used in the estimation of color from the subjective feeling. The monochrome with unique color or the unique color surrounded with the background color was presented. subject gazed the monochrome or the unique color, which was tailed target rotor. The target and background color were the complementary color each other. The various ratios of the area of gazed color and background were taken. Subject answered the level of subjective feeling consisted of pair of adjective items for unique color presented. With the use of the subjective feeling for the target color presented, the estimation of the unique color was cai\ulcornerlied out due to Fuzzy theory and neural networks. The results of color difference between unique color presented and the estimated color gave very small value for the case without background, while the results of the case with background color depended on the ratio of area of presented color and background color till the ration of 2:1, The relation showed the Kirschman's law, The color difference saturated In the increase of area of background with the ratio more than 2:1.

• Restorative Dentistry and Endodontics
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• v.25 no.1
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• pp.71-77
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• 2000

The color of an esthetic restorative material is controlled primarily by thickness of the material and background color. Although the effects of the two factors on the color coordinates of esthetic dental materials have been reported, the mechanism has not been clarified well enough to explain the effects quantitatively. The purpose of this study was to evaluate the effect of thickness and background color on the color of tooth colored restorative materials quantitatively. One hundred sixty samples were fabricated from two commercial light-cured composite resins and two commercial compomers. The color characteristics and changes in the color coordinates were measured by a tristimulus colorimeter (Model TC-6FX, Tokyo Denshoku Co. Japan) using the CIELAB system. The results were as follows: 1. As thickness increased from 1.0 to 4.0mm, values of $L^*$ $a^*$ $b^*$ changed irregulary for white and dentin color background, but showed no obvious difference in color for black background. 2. The colors of composite resins and compomers were significantly influenced by background color. 3. The color difference was recognized even the same shade name in four representative kinds of composite resins and compomers. 4. As thickness changed, values of color difference for same products and same background color showed constancy, but showed difference for different background color.

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.131-140
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• 2017

As video equipments such as CCTV are used for various purposes in fields of society, digital video data processing technology such as automatic motion detection is essential. In this paper, we proposed and implemented a more stable and accurate motion detection system based on background subtraction technique. We could improve the accuracy and stability of motion detection over existing methods by efficiently processing color information of digital image data. We divided the procedure of color information processing into each components of color information : brightness component, color component of color information and merge them. We can process each component's characteristics with maximum consideration. Our color information processing provides more efficient color information in motion detection than the existing methods. We improved the success rate of motion detection by our background update process that analyzed the characteristics of the moving background in the natural environment and reflected it to the background image.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.39-42
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• 2003

In this paper, we propose a background segmentation method in low resolution color image. A segmentation algorithm is based on color and edge information. In edge image, adaptive and local thresholds are applied to suppress paint boundaries. Through our experiments, the proposed algorithm efficiently segments background from objects.

• Fashion & Textile Research Journal
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• v.19 no.5
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• pp.653-660
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• 2017

Recently, consumers' evaluation and purchase of online design has been increasing due to the popularization of designing through personal computers, but there has not been enough studies on consumers' brain wave responses depending on the change of PC monitor's color. Therefore, this study investigated how brain waves changed when different background colors with gray patterns were presented through PC monitors. Six background colors with same tone of slightly low saturation were selected, including ivory, yellow, pink, green, blue and pure white as a base color. The brightness and characteristics of color used were analyzed using the luminance meter and color scales. Brain wave was measured by EEG measurement equipment. Brain wave measurement was carried out with 9 subjects at 6 points: F3, F4, T3, T4, O1, and O2. Stimuli were shown for 15 seconds each and black screens were displayed for 15 seconds between each stimulus. As results, the brain waves at O1 responded sensitively by different background colors, followed by F4 and T4. Brain index such as 'RT', 'RA', 'RG', 'RSA', and 'RAHB' showed significant differences depending on the background color at O1, whereas 'RST' differed at F4. Yellow and blue backgrounds pair was the only stimuli that showed significant differences in six brain indices mentioned. Yellow background had higher value of 'RG' at O1 and higher 'RST' at F4, indicating yellow background enhanced concentration. Blue background activated 'RT', 'RA', 'RSA', 'RAHB' at O1, meaning blue background induced calm and stable state.

• Korean Journal of Optics and Photonics
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• v.9 no.1
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• pp.38-46
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• 1998

In this study, the color reproduction algorithm considering both of luminace and chromaticity of the background light is presented and tested to BT-H 1450 monitor(Panasonic). In the case of neglecting the background effect, the Macbeth ColorChecker's 24 colors are reproduced with the average color difference ${\Delta}E_{ab}^{*}$ more than 9.0. By using this method, the average color difference ${\Delta}E_{ab}^{*}$ is decreased less than 1.0. From this study, we can find that both of luminance and chromaticity of background light are very important factors in the color reproduction on a CRT display.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.347-350
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• 2011

This paper propose a statistical color model of background extraction base on Hue-Saturation-Value(HSV) color space, instead of the traditional RGB space, and shows that it provides a better use of the color information. HSV color space corresponds closely to the human perception of color and it has revealed more accuracy to distinguish shadows [3] [4]. The key feature of this segmentation method is based on processing hue component of color in HSV color space on image area. The HSV color model is used, its color components are efficiently analyzed and treated separately so that the proposed algorithm can adapt to different environmental illumination condition and shadows. Polar and linear statistical operations are used to calculate the background from the video frames. The experimental results show that the proposed background subtraction method can automatically segment video objects robustly and accurately in various illuminating and shadow environments.

• Science of Emotion and Sensibility
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• v.17 no.2
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• pp.35-44
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• 2014

The purpose of this paper is to investigate the readability of Nearly White background color in display environment. To perform the experiment, warmup experiment was carried out to for cognitive of whiteness using a Tablet PC. The experiment environment was by a indoor window seat under a mixture of fluorescent light and sunlight. The result of previous test was that the most whiteness perception was a color white a medium wavelength and followed by the short wavelength. The main experiment was to find readability, color combination and visual strains using 4 nearly whites background colors (Reddish, Greenish, Blueish, Yellowish) and one white background color, also text color is limited on black. As a result, readability and color combination had the highest score against a Greenish white background. Visual strain is also the lowest against a Greenish background. On the contrary, readability and color combination preference has the lowest score against the Reddish background. Visual strain is also the highest against a Reddish background. We propose the background color, which improves readability and reduces visual strain in visual display terminals environment through the research results.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.31-38
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• 2009

A process of identifying moving objects from data is typical task in many computer vision applications. In this paper, we propose a motion segmentation method that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter (AMF) was chosen to perform background modelling. To demonstrate the effectiveness of proposed approach, we tested it gray-scale video data as well as RGB color space.