• Journal of The Korean Association of Information Education
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• v.3 no.1
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• pp.134-142
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• 1999

The demand for recognizing the color as well as the object shape is increasing to use the detailed information, because-the expense of color input/output devices become cheap. The research on the color correction should be researched for the exact color presentation and color reproduction of color input/output systems. In this paper, we researched on the color correction of color scanner. The characterization of color scanner is a two step process of gray-balancing and color transformation. The decoupling of the gray-balancing from the color transformation enables the portability of the scanner characterization. We used the least square methods for the line fitting and the Neural Network for the storage space and computation speed. The output of Neural Network is similar to the target value in three-dimensional tristimulus space. The proposed color correction method can be used for all scanners of a manufacturer's model because of the portability.

• Journal of the Semiconductor & Display Technology
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• v.23 no.2
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• pp.23-27
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• 2024

Underwater images are typically degraded due to color distortion, light absorption, scattering, and noise from artificial light sources. Restoration of these images is an essential task in many underwater applications. In this paper, we propose a two-phase deep learning-based method, Underwater Deep Curve Estimation (UWDCE), designed to effectively enhance the quality of underwater images. The first phase involves a white balancing and color correction technique to compensate for color imbalances. The second phase introduces a novel deep learning model, UWDCE, to learn the mapping between the color-corrected image and its best-fitting curve parameter maps. The model operates iteratively, applying light-enhancement curves to achieve better contrast and maintain pixel values within a normalized range. The results demonstrate the effectiveness of our method, producing higher-quality images compared to state-of-the-art methods.

• Journal of the Optical Society of Korea
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• v.17 no.6
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• pp.506-512
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• 2013

Recently, the color separation issue of wide-spreading white LEDs has attracted attention due to their wide applicability as light sources in direct-lit LCD backlights. These wide-spreading LED packages usually consist of LED chips, a color-conversion phosphor layer, and a light-shaping lens. The technical aspect of this color issue was related to a method for balancing the yellow spectral component emitting from phosphors with respect to the blue one from the LED chip as a function of viewing angle. In this study, we suggested an approach for carrying out quantitative analysis for the color separation problem occurring in wide-spreading LED packages by optical simulation. In addition, the effect of an internal scattering layer on the color uniformity was investigated, which may be considered as a potential solution for this problem.

• Agricultural and Biosystems Engineering
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• v.4 no.1
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• pp.16-21
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• 2003

In the agricultural field, a machine vision system has been widely used to automate most inspection processes especially in quality grading. Though machine vision system was very effective in quantifying geometrical quality factors, it had a deficiency in quantifying color information. This study was conducted to evaluate color of beef using machine vision system. Though measuring color of a beef using machine vision system had an advantage of covering whole lean tissue area at a time compared to a colorimeter, it revealed the problem of sensitivity depending on the system components such as types of camera, lighting conditions, and so on. The effect of color balancing control of a camera was investigated and multi-layer BP neural network based color calibration process was developed. Color calibration network model was trained using reference color patches and showed the high correlation with L*a*b* coordinates of a colorimeter. The proposed calibration process showed the successful adaptability to various measurement environments such as different types of cameras and light sources. Compared results with the proposed calibration process and MLR based calibration were also presented. Color calibration network was also successfully applied to measure the color of the beef. However, it was suggested that reflectance properties of reference materials for calibration and test materials should be considered to achieve more accurate color measurement.

• Journal of Biosystems Engineering
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• v.32 no.3
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• pp.160-165
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• 2007

This study was conducted to evaluate beef using a color machine vision system. The machine vision system has an advantage to measure larger area than a colorimeter and also could measure other quality factors like distribution of fats. However, the machine vision measurement is affected by system components. To measure the beef color with the machine vision system, the effect of color balancing control was tested and calibration model was developed. Neural network for color calibration which learned reference color patches showed a high correlation with colorimeter in L*a*b* coordinates and had an adaptability at various measurement environments. The trained network showed a very high correlation with the colorimeter when measuring beef color.

• Journal of architectural history
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• v.6 no.3 s.13
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• pp.155-166
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• 1997

This study aimes to understand the principles in Theo Van Doesburg's architectural concept. Generally, Theo Van Doesburg has been thought that he betrayed De Stijl by acting contrary to the Neo-Plasticism which was constituted in early De Stijl by Mondrian and himself and by suggesting opposite one, Elementarism. Therefore this study tried to understand the principles that make his architectural concept, confirming the background of Elementarism. After studing relation, which Theo Van Doesburg has used, between space and color, it is concluded that he has unchanged principles of architectural concept from early De Stijl to last, opposite to general appreciation. So, Theo Van Doesburg acted to maintain equilibrium that exists for balancing the two elemental forces which contrast each other in relation between space and color. The equilibrium which he looked for aims to constitute harmonized dynamic space by dynamic rythem of equilibrium instead of Neo-Plastic effect. And using color, which used to be producing dynamic effect, he intended to maintain static effect for making dynamic rythem of equllibrium by the principles he made.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.140-145
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• 2009

Significant attention has recently been drawn to human robot interaction system that uses face detection technology. The most conventional face detection methods have applied under pixel domain. These pixel based face detection methods require high computational power. Hence, the conventional methods do not satisfy the robot environment that requires robot to operate in a limited computing process and saving space. Also, compensating the variation of illumination is important and necessary for reliable face detection. In this paper, we propose the illumination invariant face detection that is performed under the compressed domain. The proposed method uses color balancing module to compensate illumination variation. Experiments show that the proposed face detection method can effectively increase the face detection rate under existing illumination.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.87-94
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• 2007

Imbalances in focus, luminance and color between stereo Pairs could cause disparity vector estimation error and increment of transmission data. If the distribution of errors in residual image is large, it may influence to lowering of compression performance. Therefore, in this paper, we propose an efficient balancing method between stereo pairs to reduce the effect. For this, we registrated stereo images using a FFT based method to consider the pixels in the occluded region, we eliminated the pixels of blocks which has large error of disparity vector estimation in balancing function estimation. The balancing function has estimated using histogram specification, local information of target image and residual image between stereo images. Experiments show that the proposed method is effective in error distribution, PSNR and disparity vector estimation. We expect that our method can be improving compression efficiency in stereo coding system.

• Journal of Fashion Business
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• v.9 no.2
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• pp.20-27
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• 2005

To find suitable color for an individual is very important in personal image-making. In recent years, the importance and role of personal image is also more emphasized. This study deals with the necessity d personal color system and the proposal of color which looks nice on a person as a result d personal color system. It also includes the method of making personal image by balancing between and using both favorite color and unfavorite color. Besides, I study how does the color image affect the personal appearance image in this paper. From clinical experiments, I concluded as follow. First, Each person has his suitable color. When the color is used, the color, pimples, flows and so on are covered and defects of his face are made up for. Second, By changing the factors of his own original color-group and decision factors - color d skin, hair, eye, etc -, I can change personal color-group. Third, The image of color affects the personal appearance image, when it used in make-up and hair-color. Considering above results, If one uses one's suitable color, one will complement defects done's face and improve merits of one's. Besides, One will be more confident and active by using one's suitable color.

• Journal of Digital Contents Society
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• v.19 no.7
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• pp.1397-1403
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• 2018

Today, modern people perceive skin care as part of their physical health care, and acne is a common skin disease problem that is found on the face. In this paper, an effective acne detection algorithm using CIE $L^*a^*b^*$ color space has been proposed. It is red when the pixel value of the component image $a^*$ is a positive number, so it is suitable for detecting acne in skin image. First, the skin image based on the RGB color space is subjected to light compensation through color balancing, and converted into a CIE $L^*a^*b^*$ color space. The extracted component image $a^*$ was normalized, and then the skin and acne area were estimated with the threshold values. Experimental results show that the proposed method detects acne more effectively than the conventional method based on brightness information, and the proposed method is robust against the reflected light source.