• Proceedings of the Korean Printing Society Conference
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• 2000.12a
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• pp.0.2-0
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• 2000

Most important step for the color matching in scanner is the color coordinate transformation from the scanner RGB space to device independent uniform color space. A variety of color calibration technologies have been developed for input device. Linear or nonlinear matrices have been conveniently applied to correct the color filter\`s mismatch with color matching function in scanners. The color matching accuracy is expected to be further improved when the nonlinear matrices are optimized into subdivided smaller color spaces than in single matrix of the entire color space. This article proposed the scanner calibration method using subspace division regression analysis and it were compared with conventional method.

• Journal of the Korean Graphic Arts Communication Society
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• v.24 no.1
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• pp.23-34
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• 2006

Color reproduction is one of the most important expression factors in digital printing. In this paper, an experiment was done where the characteristics of color reproduction in digital printing. The results could summarized as follows. The printing used device profile showed a color difference of less than printing used default value in digital printing. As a result of weighting color difference, a difference between color gamut of digital original and color gamut of printing, when transforming the RGB color space to CMY color space, a exclusion the gray revision. The solution is to optimize the color transformation by gamut mapping and gray revision.

• Journal of the Korean Graphic Arts Communication Society
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• v.19 no.1
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• pp.4-16
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• 2001

Most important step for the color matching in scanner is the color coordinate transformation from the scanner RGB space to device independent uniform color space. A variety of color calibration technologies have been developed for input device. Linear or nonlinear matrices have been conveniently applied to correct the color filter's mismatch with color matching function in scanners. The color matching accuracy is expected to be further improved when the nonlinear matrices are optimized into subdivided smaller color spaces than in single matrix of the entire color space. This article proposed the scanner calibration method using subspace division regression analysis and it were compared with conventional method.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1641-1648
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• 2017

The main purpose of this paper is to compare the performances of various filters with color images to remove the noise. Furthermore, we suggest a modified de-noising process by the transformation of color model from RGB to another color models, such as HSV and $YC_BC_R$, to improve the quality of de-noising methods encompassing Median, Wiener, and Mean filters. Neither the performance comparison of the de-noising filters with color images nor the converting the color model for better de-noise on the degraded images haven't been performed before. Inspired to make improvements, we conduct experiments with new de-noising process on color images. The result of the experiments is shown that it could assist on certain filters being more reliable techniques.

• Proceedings of the Korean Printing Society Conference
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• 2002.05a
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• pp.3-9
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• 2002

• Journal of Korea Multimedia Society
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• v.19 no.12
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• pp.1936-1942
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• 2016

This paper presents a mobile color-compensating application using a RGB color compensation algorithm. The proposed application enables color vision deficiencies to differentiate images which cannot be distinguished by them. The suggested mobile application has two functions: converting images taken by camera and converting contents in the device screen. The proposed application is computationally inexpensive, since it does not require color space transformation. Simulation results show that the proposed application enables color vision deficiencies to receive information expressed by colors such as subway line maps.

• Proceedings of the Korean Printing Society Conference
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• 2000.04a
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• pp.45-55
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• 2000

Recently, as the prepress mainstream is changed to the digital wolkflow, various digital proofing systems such as high price dye sublimation printers and low price ink jet printers are widely used in printing industry. Generally, CRT monitors are also often used as a soft proofing device for hard-copy image output. However, displayed color image on CRT monitor does not match to the actual color printing sheets. Because, the color space of CRT monitor used RGB color space, and it is differ with printing device color space, CMY. Therefore, proper color compensations are needed to match the colors between hard-copy proofs on the printing device and soft copy proofs on the monitor. For the proper compensation, we used LUT and gamut mapping method for color space transformation between device dependent color space and device independent color space, vis a vis. This paper shows the application method and the usefulness of CRT monitor for the soft-copy proofing using the output characteristics of printing device.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.9-16
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• 2018

Images with lower illumination from the light source or with dark regions due to shadows, etc., can improve subjective image quality by using retinex-based image enhancement schemes. The retinex theory is a method that recognizes the relative lightness of a scene, rather than recognizing the brightness of the scene. The way the human visual system recognizes a scene in a specific position can be in one of several methods: single-scale retinex, multi-scale retinex, and multi-scale retinex with color restoration (MSRCR). The proposed method is based on the MSRCR method, which includes a color restoration step, which consists of three phases. In the first phase, the existing MSRCR method is applied. In the second phase, the dynamic range of the MSRCR output is adjusted according to its histogram. In the last phase, the proposed method transforms the retinex output value into the display dynamic range using a logarithm transformation function considering human visual system characteristics. Experimental results show that the proposed algorithm effectively increases the subjective image quality, not only in dark images but also in images including both bright and dark areas. Especially in a low lightness image, the proposed algorithm showed higher performance improvement than the conventional approaches.

• Journal of Powder Materials
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• v.20 no.3
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• pp.210-214
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• 2013

This manuscript reports on compared color evolution about phase transformation of ${\alpha}-FeOOH@SiO_2$ and ${\beta}-FeOOH@SiO_2$ pigments. Prepared ${\alpha}$-FeOOH and ${\beta}$-FeOOH were coated with silica for enhancing thermal properties and coloration of both samples. To study phase and color of ${\alpha}$-FeOOH and ${\beta}$-FeOOH, we prepared nano sized iron oxide hydroxide pigments which were coated with $SiO_2$ using tetraethylorthosilicate and cetyltrimethyl-ammonium bromide as a surface modifier. The silica-coated both samples were calcined at high temperatures (300, 700 and $1000^{\circ}C$) and characterized by scanning electron microscopy, CIE $L^*a^*b^*$ color parameter measurements, transmission electron microscopy and UV-vis spectroscopy. The yellow ${\alpha}$-FeOOH and ${\beta}$-FeOOH was transformed to ${\alpha}-Fe_2O_3$ with red, brown at 300, $700^{\circ}C$, respectively.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1040-1046
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• 2015

This paper introduces GP(Genetic Programming) based color detection model for an object detection of humanoid robot vision. Existing color detection methods have used linear/nonlinear transformation of RGB color-model. However, most of cases have difficulties to classify colors satisfactory because of interference of among color channels and susceptibility for illumination variation. Especially, they are outstanding in degraded images from robot vision. To solve these problems, we propose illumination robust and non-parametric multi-colors detection model using evolution of GP. The proposed method is compared to the existing color-models for various environments in robot vision for real humanoid Nao.