Expanding the color gamut of inkjet textile printing during color matching

Abstract. In order to study the color matching effect of ink-jet printing press under different color management systems. I applied EFI and ORIS series color management soft wares separately to the same Epson ink-jet printer and optimized the proofing with exploring the most reasonable settings. After that, I will compare the gamut and color difference in a special color management module, and also make a contrast with a standard color gamut to check the color matching effect. The results show that the average color differences of the two soft wares are all below 1.0. However, differences measured by ORIS is lower, falling to 0.5 only, which implies the proofing under ORIS color management is more similar to the presswork and more stable.

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Improve neural network-based color matching of inkjet textile printing by classification with competitive neural network

Color Research & Application ◽

10.1002/col.22246 ◽

2018 ◽

Vol 44 (1) ◽

pp. 65-72

Author(s):

Abbas Hajipour ◽

Ali Shams-Nateri

Keyword(s):

Neural Network ◽

Color Matching ◽

Competitive Neural Network ◽

Textile Printing

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Development of a color matching algorithm for digital transfer textile printing using an artificial neural network and multiple regression

Textile Research Journal ◽

10.1177/0040517515569525 ◽

2015 ◽

Vol 85 (10) ◽

pp. 1076-1082 ◽

Cited By ~ 4

Author(s):

Jong Pil Hwang ◽

Sungmin Kim ◽

Chang Kyu Park

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Multiple Regression ◽

Color Matching ◽

Matching Algorithm ◽

Textile Printing ◽

Artificial Neural

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Study of Spot-Color-Matching in Gravure

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.312.542 ◽

2013 ◽

Vol 312 ◽

pp. 542-545 ◽

Cited By ~ 1

Author(s):

Yan Zhang ◽

Shi Sheng Zhou ◽

Cong Jun Cao ◽

Bing Feng

Keyword(s):

Color Matching ◽

Color Gamut ◽

Matching Effect ◽

University Of Technology ◽

Spot Color ◽

Printing Speed

This paper expands the study of XUT-CAPT-V2.1 System, which developed by Xian University of Technology. It analyzes how the different factors, including additive (diluent), substrates, printing pressure and printing speed, influence the reproduction of spot color matching in gravure. The results show that it must firstly ensure the accuracy of color matching trend with the deliquating of the three primary colors, which use for matching in the experiments, and then keep the color matching effect as accurate as possible and the color gamut as wide as possible. On different substrates, the printing effect is different with the same ink. The density of ink is changed in according to different printing pressure and speed.

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A testing paradigm for quantifying ICC profilers

Color and Imaging Conference ◽

10.2352/issn.2169-2629.2019.27.15 ◽

2019 ◽

Vol 2019 (1) ◽

pp. 80-85

Author(s):

Pooshpanjan Roy Biswas ◽

Alessandro Beltrami ◽

Joan Saez Gomez

Keyword(s):

Digital Camera ◽

Visual Assessment ◽

Just Noticeable Difference ◽

Color Management ◽

Color Gamut ◽

Gamut Mapping ◽

Digital File ◽

Mapping Process ◽

Testing Paradigm

To reproduce colors in one system which differs from another system in terms of the color gamut, it is necessary to use a color gamut mapping process. This color gamut mapping is a method to translate a specific color from a medium (screen, digital camera, scanner, digital file, etc) into another system having a difference in gamut volume. There are different rendering intent options defined by the International Color Consortium [5] to use the different reproduction goals of the user [19]. Any rendering intent used to reproduce colors, includes profile engine decisions to do it, i.e. looking for color accuracy, vivid colors or pleasing reproduction of images. Using the same decisions on different profile engines, the final visual output can look different (more than one Just Noticeable Difference[16]) depending on the profile engine used and the color algorithms that they implement. Profile performance substantially depends on the profiler engine used to create them. Different profilers provide the user with varying levels of liberty to design a profile for their color management needs and preference. The motivation of this study is to rank the performance of various market leading profiler engines on the basis of different metrics designed specifically to report the performance of particular aspects of these profiles. The study helped us take valuable decisions regarding profile performance without any visual assessment to decide on the best profiler engine.

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Change of color appearance due to extremely high light level: corresponding colors under 100 and 3000 cd/m2

Color and Imaging Conference ◽

10.2352/issn.2169-2629.2019.27.58 ◽

2019 ◽

Vol 2019 (1) ◽

pp. 320-325 ◽

Cited By ~ 1

Author(s):

Wenyu Bao ◽

Minchen Wei

Keyword(s):

Light Level ◽

Limited Range ◽

High Light ◽

Color Preference ◽

Color Appearance ◽

Appearance Model ◽

Color Matching ◽

Light Levels ◽

Appearance Models ◽

Psychophysical Study

Great efforts have been made to develop color appearance models to predict color appearance of stimuli under various viewing conditions. CIECAM02, the most widely used color appearance model, and many other color appearance models were all developed based on corresponding color datasets, including LUTCHI data. Though the effect of adapting light level on color appearance, which is known as "Hunt Effect", is well known, most of the corresponding color datasets were collected within a limited range of light levels (i.e., below 700 cd/m2), which was much lower than that under daylight. A recent study investigating color preference of an artwork under various light levels from 20 to 15000 lx suggested that the existing color appearance models may not accurately characterize the color appearance of stimuli under extremely high light levels, based on the assumption that the same preference judgements were due to the same color appearance. This article reports a psychophysical study, which was designed to directly collect corresponding colors under two light levels— 100 and 3000 cd/m2 (i.e., ≈ 314 and 9420 lx). Human observers completed haploscopic color matching for four color stimuli (i.e., red, green, blue, and yellow) under the two light levels at 2700 or 6500 K. Though the Hunt Effect was supported by the results, CIECAM02 was found to have large errors under the extremely high light levels, especially when the CCT was low.

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