• Korean Journal of Cognitive Science
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• v.15 no.4
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• pp.21-30
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• 2004

Additive color mixture of two different background colors appeared in the afterimage of a gray circle centered on an isoluminant bichromatic background (red/green, blue/green, or blue/yellow background). The chromatic mixture still appeared in the afterimage of a gray circle on a bichromatic background at different luminance levels, and also appeared in a large test field. The saturation of the induced color was observed to increase as the overall luminance of adaptation background stimulus increase of the size of test field decreases. It was found that the chromatic mixture does not appear with a chromatic or achromatic boundary inserted on the center of the test field. The boundary seems to prevent the induced color on each side of test field from spreading to the other side so that the induced color does not appear mixed but divided into two different colors. Without a boundary on the test stimulus, the color information induced in the afterimage seems to be too weak to create a subjective boundary between the two colors and consequently propagate inward appearing mixed.

• Safety and Health at Work
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• v.8 no.2
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• pp.151-155
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• 2017

Background: At the entrance of a tunnel, reflection of sunlight from the surrounding environment and a lack of adequate lighting usually cause some vision problems. The purpose of this study was to perform a safety evaluation of lighting on a very long road in Ilam, Iran. Methods: The average luminance was measured using a luminance meter (model S3; Hagner, Solna, Sweden). A camera (model 108, 35-mm single-lens reflex; Yashica, Nagano, Japan) was used to take photographs of the safe stopping distance from the tunnel entrance. Equivalent luminance was determined according to the Holliday polar diagram. Results: Considering the average luminance at the tunnel entrance ($116.7cd/m^2$) and using Adrian's equation, the safe level of lighting at the entrance of the tunnel was determined to be 0.7. Conclusion: A comparison between the results of the safe levels of lighting at the entrance of the tunnel and the De Boer scale showed that the phenomenon of black holes is created at the tunnel entrance. This may lead to a misadaptation of the drivers' eyes to the change in luminance level at the entrance of the tunnel, thereby increasing the risk of road accidents in this zone.

• Science of Emotion and Sensibility
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• v.16 no.2
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• pp.195-206
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• 2013

The main causes of traffic accidents while driving a car is of the driver's visual distraction. In this study, the color sensitivity of the information projected on the windshield were evaluated for HUD (Head Up Display) system which helps the driver's eyes on the road while driving. The driving Information were projected $9^{\circ}$ downward from front sight $0^{\circ}$ under lab's fluorescent lights, LED floorlights and the TV had having 25 [lux] illumination when driving at night environment and 100,000 [lux] of daylight environment. Munsell color hue of the basic five colors (R, Y, G, B, P) and the color of traffic lights YR, W were the color of the seven characters, each character were outlined by White, Gray except for W. Total of 19 experimental stimuli was shown in the environment of day and night driving for asking visibility information of color, fatigue, preferences, and evaluate the degree of interference. The results came out that the bright Y and G color is visibility significantly for daylight. Second, with the outline of the text, the color of the outline works as a background for luminance contrast effects and affects visibility. Third, without the outline, the glass in front of the vehicle acts as the background and the luminance contrast of characters achieve greater brightness and visibility. The luminance contrast between the stimuli and background should be considered for increasing color visibility for driving information which is an important factor for HUD commercialization.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1077-1080
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• 2009

In this paper, we propose a new method for measuring image sticking of an OLED display using a human visual test. We determined that the perceptual image sticking threshold is 2% of luminance difference at 200 nits and 1% at 100 nits, respectively. Color shift must also be considered when evaluating image sticking, as a ${\Delta}$(u', v') shift of just over 0.002 can be recognized regardless of background brightness. Perception of image sticking is affected by the background level, test pattern, and ambient illumination conditions. The evaluation standard must consider both luminance variation and color shift simultaneously.

• 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.

• 한국정보디스플레이학회:학술대회논문집
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• 2002.08a
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• pp.613-616
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• 2002

Luminance and contrast ratio is one of the most fundamental and important parameters of plasma display panel. Understanding the effects of cell design parameters on the display and background luminance is inevitable for improving the contrast ratio. We report the experimental results on the relationships between cell parameters and contrast ratio of the ac PDP driven by ADS scheme. It was found that the contrast ratio is the most significantly affected by rib height and optimum range of the rib height simultaneously affects the facing discharge during the reset periods, diffusion loss of plasma and shadowing of the visible light emitted from phosphor.

• Proceedings of the KIEE Conference
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• 2002.07c
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• pp.1640-1643
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• 2002

Image sticking, the phenomenon that the previously displayed pattern still remains after the image is changed into different image, is one of the most serious problem in realizing high picture quality. In this paper, we tried characterizing this undesirable feature in terms of the luminance and the intial firing voltage at ramp up time in reset period. It was found that the cell located at the boundary of previous image pattern show low firing voltage and high background luminance. And the results show that the degree of the image sticking is severely affected by discharge duration and the length of the sustain period.

• Journal of IKEEE
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• v.27 no.3
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• pp.340-344
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• 2023

In this paper, we propose a study on the development of deep learning structure to secure visibility of outdoor LED display board according to weather change. The proposed technique secures the visibility of the outdoor LED display board by automatically adjusting the LED luminance according to the weather change using deep learning using an imaging device. In order to automatically adjust the LED luminance according to weather changes, a deep learning model that can classify the weather is created by learning it using a convolutional network after first going through a preprocessing process for the flattened background part image data. The applied deep learning network reduces the difference between the input value and the output value using the Residual learning function, inducing learning while taking the characteristics of the initial input value. Next, by using a controller that recognizes the weather and adjusts the luminance of the outdoor LED display board according to the weather change, the luminance is changed so that the luminance increases when the surrounding environment becomes bright, so that it can be seen clearly. In addition, when the surrounding environment becomes dark, the visibility is reduced due to scattering of light, so the brightness of the electronic display board is lowered so that it can be seen clearly. By applying the method proposed in this paper, the result of the certified measurement test of the luminance measurement according to the weather change of the LED sign board confirmed that the visibility of the outdoor LED sign board was secured according to the weather change.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1121-1135
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• 2005

This paper proposes a moving object extraction method using the contrast map and salient points. In order to make the contrast map, we generate three-feature maps such as luminance map, color map and directional map and extract salient points from an image. By using these features, we can decide the Attention Window(AW) location easily The purpose of the AW is to remove the useless regions in the image such as background as well as to reduce the amount of image processing. To create the exact location and flexible size of the AW, we use motion feature instead of pre-assumptions or heuristic parameters. After determining of the AW, we find the difference of edge to inner area from the AW. Then, we can extract horizontal candidate region and vortical candidate region. After finding both horizontal and vertical candidates, intersection regions through logical AND operation are further processed by morphological operations. The proposed algorithm has been applied to many video sequences which have static background like surveillance type of video sequences. The moving object was quite well segmented with accurate boundaries.

• 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.