• Journal of Korean Ophthalmic Optics Society
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• v.6 no.1
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• pp.139-144
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• 2001

In order to analyze of the color perception Farnsworth Test Panel D-15 in the CIELab color space coordinates, it was measured by the reflectance spectrum of the 380~780nm wavelength regions. The Test Panel D-15 was situated in the near origin point of higher the saturation in CIELab coordinates (a, b). Normal person perceived to the similar color for the color of small color difference, and color deficiency person depended on the confusing color line and the neutral point unconcerned with the color difference. In case of Ptotanopia, Deutrnopia, r-g defect, y-b defect with the color deficiency, the neutral points position (a,b) were each (2.12,1.02), (4.25,2.05), (2.51,0.25), (1.20,-1.10).

• Journal of the Korean Graphic Arts Communication Society
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• v.19 no.2
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• pp.58-67
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• 2001

Gamut mapping is a technique that acts on cross-media color reproduction to transform a color between devices for the purpose of enhancing the appearance or preserving the appearance of an image. Gamut mapping essentially produces color conversion error which depends the gamut mapping method, source and destination devices, and sample points for gamut modeling. For color space conversion between monitor colors and printer colors, empirical representation using sample measurements is currently widely utilized. Color samples are uniformly selected in the device space such as CMY or RGB, represented as color patches, and then measured. However, in the case of printer, these color samples are not evenly distributed inside the printer gamut and the color conversion error is increased. Accordingly, this paper introduces a equally distributed color sampling method in CIELAB space, a device- independent color space, to reduce color conversion error, and the performance is analyzed via color space conversion experiments using tetrahedral interpolation.

• Proceedings of the Korean Printing Society Conference
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• 2000.12a
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• pp.0.3-0
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• 2000

Gamut mapping is a technique that acts on cross-media reproduction to transform a color between devices for the purpose of enhancing the appearance or preserving the appearance of an image. Gamut mapping essentially produces color conversion error which depends the gamut mapping method, source and destination devices, and sample points for gamut modeling. For color space conversion between monitor colors and printer colors, empirical representation using sample measurements is currently widely utilized. Color samples are uniformly selected in the device space such as CMY or RGB, represented as color patches, and then measured. However, in the case of printer, these color samples are not evenly distributed inside the printer gamut and the color conversion error is increased. Accordingly, this paper introduces a equally distributed color sampling method in CIELAB space, a device-independent color space, to reduce color conversion error, and the performance is analyzed via color space conversion experiments using tetrahedral interpolation.

• Journal of Korea Multimedia Society
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• v.4 no.4
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• pp.316-323
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• 2001

Gamut mapping is a technique that acts on cross-media color reproduction to transform a color between devices for the purpose of enhancing the appearance or preserving the appearance of an image. Gamut mapping essentially produces color conversion error which depends on the gamut mapping method, source and destination devices, and sample points for gamut modeling. For color space conversion between monitor colors and printer colors, empirical representation using sample measurements is currently widely utilized. Color samples are uniformly selected in the device space such as CMY or RGB, represented as color patches, and then measured. However, in the case of printer, these color samples are not evenly distributed inside the printer gamut and the color conversion error is increased. Accordingly, this paper introduces a equally distributed color sampling method in CIELAB space, a device- independent color space, to reduce color conversion error, and the performance is analyzed via color space conversion experiments using three-dimensional interpolation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.1-7
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• 2011

In this paper, we propose the digital image enhancement method including local tone reproduction and preservation of the hue. In recent studies, an integrated multi-scale retinex (IMSR) has produced great naturalness in the resulting images through enhancement of visibility in dark area in input images. However, most methods, including IMSR, work in RGB color spaces. As such, this produces hue distortion from the perspective of the human visual system, that is, hue distortion in CIELAB color space. Accordingly, this paper proposes an tone reproduction and enhancement of saturation method in a device-independent color space, CIELAB, to preserve the hue and obtain a high contrast and naturalness. First, to achieve the desired objectives, the IMSR is then applied to only the $L^*$ values in CIELAB color space, normalization, and simple mapping function, thereby preserving the balance of the color components and enhancement of visibility. Then, saturation adjustment is performed by applying the ratio of the chroma variation at the sRGB gamut boundary according to the corrected luminance. In experiments, the proposed method is shown to improve the visibility in dark shadows and bright regions in the resulting images and reduce any color distortion then preference test are performed.

• Journal of the Korean Graphic Arts Communication Society
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• v.25 no.1
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• pp.121-133
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• 2007

The CMS(color management system) software was to enable consistent color reproduction from original to reproduction. The CMS was to create RGB monitor and printer characterization profiles and then use the profiles for device independent color transformation. The implemented CMM(color management module) used the CIELAB color space for the profile connection. Various monitor characterization model was evaluated for proper color transformation. To construct output device profile, SLI(sequential linear interpolation) method was used for the color conversion from CMYK device color to device independent CIELAB color space and tetrahedral interpolation method was used for backward transformation. UCR(under color removal) based black generation algorithm was used to construct CIELAB to CMYK LUT(lookup table). When transforming the CIE Lab colour space to CMYK, it was possible to involve the gray revision method regularized in the brightness into colour transformation process and optimize the colour transformation by black generation method based on UCR technique. For soft copy colour proofing, evaluating several monitor specialism methods showed that LUT algorithm was useful. And it was possible to simplify colour gamut mapping by constructing both the look-up table and the colour gamut mapping algorithm to a reference table.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.262-264
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• 2002

In this paper we focused on the color representation prob1em based on fuzzy set theory. The main factor is the determination or computation of color membership function and color difference formula. The mathematical formula to calculate the color difference should generate a uniform color scaling, and due to this reason we adopted a CIELAB color- space as a fundamental feature space. With the help of the CIELAB color space we created a new color model, referred to fuzzy color model, which can represent the ambiguous characteristics underlying colors. Based on the proposed color difference formula between fuzzy colors, we could obtain the membership computation method of an arbitrary color for a given color family.

• Journal of the Microelectronics and Packaging Society
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• v.22 no.1
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• pp.15-19
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• 2015

We demonstrated an inspection system for detecting discoloration of PCB Cu ball pad with an OSP surface finish. Though the OSP surface finish has many advantages such as eco-friendly and low cost, however, it often shows a discoloration phenomenon due to a heating process. In this study, the discoloration was analyzed with device-independent CIELAB color space. First of all, the PCB samples were inspected with standard lamps and CCD camera. The measured data was processed with Labview program for detecting discoloration of Cu ball pad. From the original PCB sample image, the localized Cu ball pad image was selected to reduce the image size by the binarization and edge detection processes and it was also converted to device-independent CIELAB color space using $3{\times}3$ conversion matrix. Both acquisition time and false acceptance rate were significantly reduced with this proposed inspection system. In addition, $L^*$ and $b^*$ values of CIELAB color space were suitable for inspection of discoloration of Cu ball pad.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1546-1549
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• 2009

In recent studies on tone reproduction with the objective of reproducing natural looking colors in digital images, an integrated multi-scale retinex (IMSR) has produced great naturalness in the resulting images. Most methods, including IMSR, work in RGB or quasi-RGB color spaces. As such, this produces hue distortion from the perspective of the human visual system. Accordingly, this paper proposes the hue preserved multi-scale Retinex (HPMSR) method to obtain a high contrast and naturalness. The proposed method enhanced the $L^*$ and saturation values in CIELAB color space. As a result, the visibility in dark shadows in the resulting images was improved.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.64-75
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• 2000

This paper proposes a color sample selection method that produces a uniform distribution in the display gamut plus a color reproduction method for using a uniform color sample In contrast to the conventional method, the proposed uniform color samples are selected m CIELAB, a device-independent color space, instead of RGB (red, green, and yellow) or CMY (cyan, magenta, and yellow) space, device-dependent color spaces To evaluate the performance of the proposed color samples, they were applied to color space conversion using both a regression model and neural network As a result, in the case of a color sample of the same size, the color space conversion method using the proposed samples showed a lower color difference for color conversions using either neural or regression.