A Euclidean color space in high agreement with the CIE94 color difference formula

2000 ◽  
Vol 25 (1) ◽  
pp. 64-65 ◽  
Author(s):  
Knud Thomsen
Keyword(s):  
Color Space ◽  
Color Difference ◽  
High Agreement ◽  
Difference Formula

Evaluation of change in color of denim fabric after various industrial washing processes with different fiber composition

2014 ◽  
Vol 11 (2) ◽  
pp. 107-110
Author(s):  
Mushtaq Mangat ◽  
A. Abbasi ◽  
Jakub Wiener
Keyword(s):  
Color Space ◽  
Color Difference ◽  
Fiber Composition ◽  
Obvious Change ◽  
Washing Machines ◽  
Difference Formula ◽  
Denim Fabric ◽  
Cielab Color

Traditional denim made by using 100% cotton and novel denim made by using cotton in warp and spun PP in the weft were treated in 11 different ways on industrial garment washing machines with the help of various textile auxiliaries and pumice. There is an obvious change in color of denim. This change was measured by using Spectrophotometer. Reflectance was taken as a variable to observe the intensity of change. Color difference was measured by using the CIELab color difference formula 1976. Color space coordinates (L*, a*, b*) and color difference ΔE were calculated between the untreated denim and treated denim.

The Color Recognition of Jet Fuel Silver Corrosion Images Based on Color Difference Formula

2012 ◽  
Vol 503-504 ◽  
pp. 1033-1036
Author(s):  
Li Ping Tong ◽  
Bin Peng ◽  
Yi Wei Fei
Keyword(s):  
Color Space ◽  
Color Difference ◽  
Recognition System ◽  
Jet Fuel ◽  
Color Spaces ◽  
Object Surface ◽  
Television System ◽  
Color Recognition ◽  
Difference Formula ◽  
Cie Lab

This article introduces the basic theoretical knowledge of the multi-color space and its color difference formula. By research and experiment, it validates that HSV and CIE L * a * b * color space and its corresponding color difference formula, which are used in the color recognition of jet fuel silver corrosion image, and their results are mostly in accordance with the recognition results by the naked eyes. And it also proves the feasibility of these two methods for the color recognition of jet fuel silver corrosion. Silver strip corrosion experiment must be tested as one of jet fuel corrosion detection items in jet fuel accepting, providing and storage process. The examination, whether jet fuel is qualified or not, is mainly due to silver corrosion’s color judgment. For computer visual system, the color is the character of object surface, and it is mankind recognition system to the object surface, light shine and visual condition’s comprehensive effect, and it has important function in the picture’s partition and identifying field. The color that is put up by visible light is continuous, and in order to measure and calculate conveniently, some scholars successively establish more than ten color spaces, which are mainly divided three types, by the HSV color space with RGB, HIS, and Munsell color spaces etc. According to particular application color space, YUV and YIQ and CMY color space are adopted by the television system, and CIE color space then includes CIE, XYZ, Lab and Luv etc. This article comparatively studies representative color space as well as RGB, HIS, CMY, YUV and CIE Lab color spaces, which are used for jet fuel silver strip corrosion image’s color recognition accuracy, and this article finally ensures a kind of color space and color difference formula which are applied to jet fuel silver strip corrosion image’s color recognition.

Contribution of Green Jadeite-Jade’s Chroma Difference Based on CIE 1976 L*a*b* Uniform Color Space

2010 ◽  
Vol 177 ◽  
pp. 620-623 ◽  
Author(s):  
Ying Guo ◽  
Jun Zhang ◽  
Tao Mo
Keyword(s):  
Color Space ◽  
Color Perception ◽  
Correlation Coefficients ◽  
Color Difference ◽  
Green Color ◽  
Difference Formula ◽  
Positive Linear Correlation ◽  
Cie Lab ◽  
Human Eyes ◽  
The Impact

The correlations between lightness and chroma, lightness difference and color difference, chroma difference and color difference were studied to evaluate the impact of lightness on color. Based on color difference formula CIE LAB in the uniform color space CIE L*a*b* it is learnt that H*ab of jadeite jade green colors has made little contribution to E*ab. Given the fact that human eyes are relatively sensitive to the color perception of lightness difference and that lightness and chroma affect each other, lightness of jadeites has been divided into two groups: while the lightness of green is relatively low (L*  19.52), lightness and chroma have positive linear correlation (correlation coefficient L*  C* = 0.971), which means the higher lightness the higher chroma and brings brighter green color; while L* > 19.52 , there is no one-to-one correspondence between lightness and chroma, and the highest chroma 77.64 can be reached when L* = 37.63. The high partial correlation coefficients L*ab  E*ab = 0.974 and C*ab  E*ab = 0.971 reveal that both L*ab and C*ab are not affected by the lightness of jadeite and are equally important to E*ab. It is concluded that the quality estimation of green color of Jadeite Jade should be primarily based on lightness which is the most intuitive factor and consistent with the color perception, and then followed by the evaluation of chroma and hue.

Evaluation Accepted Small Color-Difference Samples by Using High Glossy Ink-Jet Paper

2011 ◽  
Vol 380 ◽  
pp. 179-182
Author(s):  
Jing Liang ◽  
Ning Fang Liao ◽  
Yu Sheng Lian ◽  
Yuan Yuan Wang
Keyword(s):  
Color Vision ◽  
Color Space ◽  
Visual Assessment ◽  
Color Difference ◽  
Normal Color Vision ◽  
Visual Color ◽  
Difference Formula ◽  
Ink Jet ◽  
Human Color Vision ◽  
High Range

In order to study the human color vision characteristics, the small color-difference discrimination threshold experiment at the 17 basic CIE color centers of high range of gloss color printed samples. A panel of 10 observers with normal color vision performed the visual assessment to 510 pairs of samples using admissibility method. The evaluation data of visual color-difference were obtained in CIELAB color space. The detailed comparision indicated that the data were used evaluate the four common color-difference formula, CIELAB, CIE94, CMC and CIEDE2000. The detailed analysis indicated that CIELAB recommended by CIE Performanced the best among the four modern color difference. For predicting very small color datas. The experimental data provides references for the improvement of uniform color space and color-difference formula.

A Discussion on Printing Color Difference Tolerance by CIEDE2000 Color Difference Formula

2012 ◽  
Vol 262 ◽  
pp. 96-99 ◽  
Author(s):  
Hao Xue Liu ◽  
Bing Wu ◽  
Yu Liu ◽  
Min Huang ◽  
Yan Fang Xu
Keyword(s):  
Color Space ◽  
Color Difference ◽  
Experimental Results ◽  
Printing Industry ◽  
Cielab Color Space ◽  
Difference Formula ◽  
Different Color ◽  
Cielab Color

In ISO printing standards, a color difference tolerance of ΔE*ab=5 is used as a threshold. But CIELAB color space is not uniform enough so that the same color difference value represents different color difference sensation in different color area. It is proved that the color difference calculated by CIEDE2000 is closer to the human sensation, so ISO TC130 is discussing the possibility of replacing CIELAB color difference by CIEDE2000. An experiment was conducted, in which the color difference of typical printing colors, CMYKRGB, was calculated and test. The experimental results showed that the color difference tolerance of ΔE*ab=5 is corresponding to 0.95~6.42 by CIEDE2000, with the average of 3.30 ΔE*00. So a color difference tolerance of ΔE*00=3.3 or a somewhat looser value of ΔE*00=3.5 can be adopted as a new tolerance for printing industry.

Influence of Fe2+ on the Color Appearance of Yellow-Green Peridot

2011 ◽  
Vol 492 ◽  
pp. 370-373 ◽  
Author(s):  
Wei Xi Tang ◽  
Ying Guo ◽  
Li Xia Ma
Keyword(s):  
Color Space ◽  
Chromatic Aberration ◽  
Color Difference ◽  
Color Appearance ◽  
Chemical Compositions ◽  
Significance Level ◽  
Icp Ms ◽  
Difference Formula ◽  
Chromaticity Coordinates ◽  
Cie Lab

Twenty-eight yellow-green color of uniform, high clarity and similar thickness of 5 mm × 7 mm oval faceted peridots from Jiaohe Jilin province were examined by LA-ICP-MS and Color i5 to test their chemical compositions and L*, C* and ho. The correlations between Fe2+ and color parameters were analyzed, in order to establish the influence on the color appearance of Fe2+. The chemical formula of the twenty-eight peridots is (Mg1.84,Fe0.19)2.04[(Si0.982,Al0.001)0.983O4], which was calculated by oxygen atom. It reveals that 0.19 mol Fe2+ is concluded in one mol peridot, and Fe2+ is the colorant of peridot. Based on the CIE 1976 L*a*b* uniform color space, relationships between chromaticity coordinates a*, b* and chromaticity C* were analyzed by Two-way ANOVA, of which the results showing that the influence of b* on C* (rb*×C*=0.996) is much more prominent than a* on C* (ra*×C*= -0.383). By partial correlation analysis of the results calculated through CIE LAB color-difference formula, it can be discovered that lightness difference DL* has a better correlation with chromatic aberration DE* than DC* and DH*, whereas the significance level ρDC*×DE* > 0.05, rDH*×DE* > 0.05, it reveals that DE* is more sensitive to DL*. At the same time, L* changes the most with the contributions of Fe2+ compared with other parameters of peridot. It is concluded that, with the help of L*, Fe2+ has a further influence on the color appearance of peridot.

Recent Advances in Color and Whiteness Evaluations in Dentistry

2019 ◽  
Vol 1 (1) ◽  
pp. 23-29 ◽  
Author(s):  
María M. Pérez ◽  
Oscar E. Pecho ◽  
Razvan Ghinea ◽  
Rosa Pulgar ◽  
Alvaro Della Bona
Keyword(s):  
Clinical Performance ◽  
Dental Materials ◽  
Color Space ◽  
Color Difference ◽  
Color Measurement ◽  
Tooth Color ◽  
Dental Research ◽  
Color Science ◽  
Difference Formula ◽  
Color Differences

Background: The final goal of color measurement or shade specification in dentistry is the reproduction by prosthetic materials of all important appearance characteristics of natural oral structures. The application of color science in dentistry is an objective way to measure and evaluate such structures and dental materials in clinical practice and dental research. Methods: Literature on color science was reviewed to present new metrics to evaluate color differences of dental materials and dental structures. Visual acceptability and perceptibility values of color differences are reviewed and new whiteness indexes to describe whiteness in dentistry are presented. Results: In the last decade, the CIELAB 50:50% perceptibility and acceptability thresholds were set to 1.2 and 2.7, respectively, and the CIEDE2000 50:50% perceptibility and acceptability thresholds were set to 0.8 and 1.8. The CIEDE2000 color-difference formula became increasingly popular in dentistry. Developments in color science have led to the description of tooth whiteness and changes in tooth whiteness based on whiteness indexes, with the most relevant being the WID whiteness index, which is a customized index based in CIELAB color space. Conclusion: The application of color science in dentistry has allowed the precise description of tooth color and whiteness. The revised and new CIEDE2000 color-difference formula is expected to fully replace the outdated CIELAB formula in almost all dental applications. Recent psychophysical studies have reported values of visual thresholds and new whiteness indexes, which can serve as quality control tools to guide the selection of esthetic dental materials, evaluate clinical performance, and interpret visual and instrumental findings in clinical dentistry, dental research, and subsequent standardization.

A new color difference formula in RGBcolor space

2009 ◽  
Vol 29 (2) ◽  
pp. 465-467
Author(s):  
Zhen-ya YANG ◽  
Yong WANG ◽  
Zhen-dong YANG ◽  
Cheng-dao WANG
Keyword(s):  
Color Difference ◽  
Difference Formula

scholarly journals A Study of Automatic Judgment of Food Color and Cooking Conditions with Artificial Intelligence Technology

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1128
Author(s):  
Chern-Sheng Lin ◽  
Yu-Ching Pan ◽  
Yu-Xin Kuo ◽  
Ching-Kun Chen ◽  
Chuen-Lin Tien
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Color Space ◽  
Color Difference ◽  
Color Space Conversion ◽  
Before And After ◽  
Artificial Intelligence Technology ◽  
Artificial Intelligence Algorithm ◽  
Time Image ◽  
Cooking Conditions

In this study, the machine vision and artificial intelligence algorithms were used to rapidly check the degree of cooking of foods and avoid the over-cooking of foods. Using a smart induction cooker for heating, the image processing program automatically recognizes the color of the food before and after cooking. The new cooking parameters were used to identify the cooking conditions of the food when it is undercooked, cooked, and overcooked. In the research, the camera was used in combination with the software for development, and the real-time image processing technology was used to obtain the information of the color of the food, and through calculation parameters, the cooking status of the food was monitored. In the second year, using the color space conversion, a novel algorithm, and artificial intelligence, the foreground segmentation was used to separate the vegetables from the background, and the cooking ripeness, cooking unevenness, oil glossiness, and sauce absorption were calculated. The image color difference and the distribution were used to judge the cooking conditions of the food, so that the cooking system can identify whether or not to adopt partial tumbling, or to end a cooking operation. A novel artificial intelligence algorithm is used in the relative field, and the error rate can be reduced to 3%. This work will significantly help researchers working in the advanced cooking devices.

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