• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.51-59
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• 2004

This paper proposes an improved six-color separation reducing the graininess in a middle tone region based on the standard deviation of the lightness and chrominance in S-CIELAB space. Graininess is regarded as visual perception for the fluctuation of the lightness of the light cyan and cyan or light magenta and magenta. In the conventional methods, the granularity is extremely heuristic and inaccurate due to the use of the visual examination score. Accordingly, this paper proposes a method to calculate the objective granularity for six color separation. First, we use the lightness, redness-greenness, and yellowness-blueness of the S-CIELAB space reflecting the spatial-color sensitivity of the human and normalize the sum of the three standard deviations. Finally, we apply the proposed granularity to the six color separation after assigning the granularity to the lookup table and obtain the result reducing the graininess in a middle tone region.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.33-41
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• 2004

This paper proposes a color matching 3D look-up table simplifying the complex color matching procedure between a monitor and a mobile display device. In other to perform color matching, it is necessary to process color of image in the device independent color space like CIEXYZ or CIELAB. To obtain the data of the device independent color space from that of the device dependent RGB color space, we must perform display characterizations. LCD characterization error using S-curve model is larger than tolerance error since LCD is more nonlinear than CRT. This paper improves the S-curve model to have smaller characterization error than tolerance error using the electro-optical transfer functions of X, Y, and Z value. We obtained images having higher color fidelity on mobile display devices through color matching experiments between monitor and mobile display devices. As a result of this experiments, we concluded that the color matching look-up table with 64(4${\times}$4${\times}$4) is the smallest size allowing characterization error to be acceptable.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.434-442
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• 2006

This paper proposes a color-matching 3D look-up table that simplifies the complex color-matching procedure between a monitor and a mobile display device, where the image colors are processed in a device-independent color space, such as CIEXYZ or CIELAB, and gamut mapping performed to compensate the gamut difference. The transform from a device-dependent RGB color space to a device-independent color space is implemented by performing display characterization. The mobile LCD characterization error using the S-curve model is larger than the tolerance error since the mobile LCD has the channel-chromaticity-inconstancy and channel-dependence characteristics. In this paper we reduced the characterization error using the electro-optical transfer functions of X, Y, and Z value for R, G, B, C, M, Y, K components. Experimental results demonstrated that 64 ($4{\times}4{\times}4$) was the smallest size of color-matching look-up table that could produce an image with an acceptable reproduction error, based on a comparison of color-matched images resulting from the proposed color-matching look-up table and complex step-by-step color-matching procedures.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.33-40
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• 2023

The mainstay of current image recovery frameworks is Content-Based Image Retrieval (CBIR). The most distinctive retrieval method involves the submission of an image query, after which the system extracts visual characteristics such as shape, color, and texture from the images. Most of the techniques use RGB color space to extract and classify images as it is the default color space of the images when those techniques fail to change the color space of the images. To determine the most effective color space for retrieving images, this research discusses the transformation of RGB to different color spaces, feature extraction, and usage of Convolutional Neural Networks for retrieval.

• Textile Coloration and Finishing
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• v.18 no.2 s.87
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• pp.15-23
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• 2006

A new fastness formula based on CIEDE2000 color-difference formula is developed by B. Rigg and his coworkers. It is very simple to calculate fastness grade for color change than ISO 105-A05 fastness formula based on CIELAB color-difference formula. Sample pair sets which cover a wide range color space were accumulated from NCS(Natural Color System) color book. For those sample pair sets, visual measurement experiment and instrument measurement experiment of fastness grade were carried out and each performance of ISO 105-A02 fastness formula and newly developed fastness formula was compared through degree of agreement for visual measurement result. Newly developed fastness formula indicated improved performance for measuring fastness grade but current ISO fastness formula for assessing change in color, ISO 105-A05, was confirmed that it's performance is inadequate to measure fastness grade. Then fastness formulae were examined more closely according to particular color spaces and the correlation of hue, lightness and chrom for measuring fastness grade was also considered in this study.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.25-33
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• 2006

This paper proposed device-independent color matching algorithm based on the 3D RGB lookup table (LUT) between mobile camera and mobile LCD (Liquid Crystal Display) to improve the color-fidelity. Proposed algorithm is composed of thee steps, which is device characterization, gamut mapping, 3D RGB-LUT design. First, the characterization of mobile LCD is executed using the sigmoidal function, different from conventional method such as GOG (Gain Offset Gamma) and S-curve modeling, based on the observation of electro-optical transfer function of mobile LCD. Next, mobile camera characterization is conducted by fitting the digital value of GretagColor chart captured under the daylight environment (D65) and tristimulus values (CIELAB) using the polynomial regression. However, the CIELAB values estimated by polynomial regression exceed the maximum boundary of the CIELAB color space. Therefore, these values are corrected by linear compression of the lightness and chroma. Finally, gamut mapping is used to overcome the gamut difference between mobile camera and moible LCD. To implement the real-time processing, 3D RGB-LUT is designed based on the 3D RGB-LUT and its performance is evaluated and compared with conventional method.

• Journal of the Korean Graphic Arts Communication Society
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• v.18 no.2
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• pp.29-40
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• 2000

Recently. color proofing in printing industry grow rapidly. If an order decide color from known color information in the case of color reproduction, we can reduce expenses and time. In color proofing the best important point must be closed proofed color to primary color and secondary color. Model-based approaches have the advantages of faster recharacterization and the opportunity of simulating product enhancements such as changes in ink properties and halftoning. In this paper, we transformed the dot area of CMYK to CIELAB color space using color reproduction models. Firstly, we measured spectral reflectance of primary color printed by Matchprint II and the data was used to find tone reproduction curve using regression equation, and than we applied at primary color model, such as Murray-Davies, Yule-Nilsen, and mixed color model, such as Kubelka-Munk, relaxed version of spectral Neugebauer. In such results, the Kubelka-Munk model resulted in the best spectral reconstruction accuracy followed by relaxed version of spectral Neugebauer model, color difference is 2.8401.

• Proceedings of the Korean Printing Society Conference
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• 2000.04a
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• pp.25-34
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• 2000

Recently, color proofing in printing industry grow rapidly. If an order decide color from known color information in the case of color reproduction, we can reduce expenses and time. In color proofing the best important point must be closed proofed color to primary color and secondary color. Model-based approaches have the advantages of faster recharacterization and the opportunity of simulating product enhancements such as changes in ink properties and halftoning. In this paper, we transformed the dot area of CMYK to CIELAB color space using color reprodution models. Firstly, we measured spectral reflectance of primary color printed by Matchprint II and the data was used to find tone reproduction curve using regression equation, and than we applied at primary color model, such as Murray-Davies, Yule-Nilsen, and mixed color model, such as Kubelka--Munk, relaxed version of spectral Neugebauser. In such results, the Kubleka-Munk model resulted in the best spectral reconstruction accuracy followed by relaxed version of spectral Neugebauer model, color difference is 2.8401.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.106-109
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• 2003

This paper presents a hue preserving gamut mapping algorithm for color monitor and printer. The gamuts of monitor and printer are set by the profile of color reproduction media, specified by ICC(International Color Consortium) and provided by vendors, then those gamuts are represented on the CIE xy color space. In case that the color of monitor are located on out-of-gamut of printer, these are clipped on the point of gamut boundary of printer towards a reference white point. On the other hand, colors are in-gamut of printer are unchanged. An image generated by the algorithm keeps a ratio of each pixel of original image. Advantages of the algorithm are easy to implement and fast processing time than other algorithms which involve hue preserving especially in CIELAB color space.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1759-1762
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• 2003

This paper proposes the method that design CLUT(color look-up table) simultaneously processing gamut mapping and color space conversion using only LUT without complex computation. After we construct LUT composed of scanner gamut and printer gamut, we extend L$\^$*/a$\^$*/b$\^$*/ points based on input L$\^$*/a$\^$*/b$\^$*/ to include input scanner L$\^$*/a$\^$*/b$\^$*/ Input RGB image of scanner is converted into CIEL$\^$*/a$\^$*/b$\^$*/ using regression (unction. CIELAB values of scanner are convened into CMY values including gamut mapping processing without additional gamut mapping using the proposed CLUT. In the experiments, the proposed method resulted in the similar color difference, but reduced the complexity computation compared with processing gamut mapping and color space conversion respectively