Color-Difference Threshold for Printed Images

2013 ◽  
Vol 469 ◽  
pp. 236-239
Author(s):  
Hao Xue Liu ◽  
Gui Hua Cui ◽  
Min Huang ◽  
Bing Wu ◽  
Yu Liu
Keyword(s):  
Color Difference ◽  
Psychophysical Experiment ◽  
Difference Threshold ◽  
Test Image ◽  
Color Distribution ◽  
Difference Formula ◽  
Color Differences ◽  
The Mean ◽  
Image Pairs ◽  
Test Color

Five ISO 400 images were used as test images and a method of limits psychophysical experiment was designed to test color-difference threshold in printed images. The color appearance of each original image was modified by an exponential function for CIELAB lightness and chroma, an offset function for CIELAB hue at 20 steps for each attributes respectively. The modified images and their originals were paired to form the test image pairs. The mean color differences of image pairs, ranged from 0 to 4 CIELAB units, were calculated by CIELAB color-difference formula and nearly uniformly divided into 21 grades for each attributes. The test image pairs were assessed in a CPC-8n lighting booth. 12 normal color vision observers took part in the experiment. The experimental results showed that the mean color-differences threshold for lightness, chroma and hue attributes were 1.49, 1.53 and 0.78 CIELAB units showing the threshold for hue was apparently smaller than that of lightness and chroma, and the thresholds of different images were dependent on the image content or color distribution.

Color difference formulae evaluation by method of adjustment

2014 ◽  
Vol 11 (1) ◽  
pp. 89-94 ◽  
Author(s):  
A. Abbasi ◽  
M. Vik ◽  
M. Vikova
Keyword(s):  
Color Difference ◽  
Psychophysical Method ◽  
Psychophysical Experiment ◽  
Statistical Measures ◽  
Color Differences ◽  
The Mean ◽  
Different Color ◽  
Method Of Adjustment ◽  
Visual Results ◽  
Test Color

This experiment was carried out to test color difference formulae by method of adjustment. 6 different color centers (Red, Yellow, Green, Blue-Green, Blue and Violet) were chosen for this psychophysical experiment. 336 virtual sample pairs were prepared. The mean color difference was three CIELAB units. Each pair was assessed by a panel of 15 observers using psychophysical methods called Method of Adjustment. These visual data were used to test color-difference formulae: CIELAB, CMC, CIE94, DIN99d and CIE2000 with the help of simple statistical measures i.e., PF/3 and Stress. It was found that the visual results obtained from psychophysical method of adjustment show that CIE94 as well as DIN99d still perform well for small color differences.

scholarly journals Spectrophotometric color evaluation of permanent incisors, canines and molars. A cross-sectional clinical study

2015 ◽  
Vol 88 (4) ◽  
pp. 537-544 ◽  
Author(s):  
Ioana- Sofia Pop-Ciutrila ◽  
Horatiu Alexandru Colosi ◽  
Diana Dudea ◽  
Mandra Eugenia Badea
Keyword(s):  
Color Difference ◽  
Permanent Teeth ◽  
Cross Sectional ◽  
Mean Values ◽  
Color Coordinates ◽  
Color Differences ◽  
The Mean ◽  
Maxillary Incisors ◽  
Mean Differences ◽  
Acceptability Threshold

Background and aims. An accurate color reproduction represents the final validation level of an esthetic anterior or posterior restoration. The aim of this study was to evaluate the color of permanent maxillary incisors, canines and molars, using a clinical spectrophotometer.Methods. The Vita Easyshade Advance 4.0® intraoral spectrophotometer was used by one clinician to determine the color of 369 permanent maxillary incisors, canines and molars. The best matches to Vitapan Classical® and 3D-Master® shade guides were recorded. A one-way analysis of variance and Kruskal-Wallis test were used to compare L*, a*, b*, c* and h* color coordinates among the 3 types of teeth. Differences between the mean values of all color coordinates were evaluated by use of Bonferroni corrections. Color difference (ΔE*) between incisors, canines and molars was calculated from ΔL*, Δa* and Δb* data and the results were compared to ΔE*=3.3 acceptability threshold.Results. Except for Δa* and Δh* between canines and molars, statistically significant differences among the mean differences of all color coordinates were found when the 3 types of teeth were compared by pairs. The most frequently measured shades were A1 (48.4%), respectively 1M1 (31.5%) for incisors, B3 (36.6%), respectively 2M3 (39.8%) for canines and B3 (44.7%), respectively 2M3 (52%) for molars. Incisors had the highest lightness values, followed by canines and molars. Molars were the most chromatic with the highest a* and b* values.Conclusions. Despite the limitations of this study, color differences among incisors, canines and molars were found to be statistically significant, above the clinical acceptability threshold established. In conclusion, successful esthetic restorations of permanent teeth of the same patient need an individual color assessment and reproduction of every type of tooth. 

scholarly journals A Design Method of Saturation Test Image Based on CIEDE2000

2012 ◽  
Vol 2012 ◽  
pp. 1-4 ◽  
Author(s):  
Yang Yang ◽  
Jun Ming ◽  
Nenghai Yu
Keyword(s):  
Design Method ◽  
Human Perception ◽  
Color Difference ◽  
Image Similarity ◽  
Masking Effect ◽  
Test Image ◽  
Visual Effects ◽  
Color Test ◽  
Saturation Parameter ◽  
Difference Formula

In order to generate color test image consistent with human perception in aspect of saturation, lightness, and hue of image, we propose a saturation test image design method based on CIEDE2000 color difference formula. This method exploits the subjective saturation parameterC′ of CIEDE2000 to get a series of test images with different saturation but same lightness and hue. It is found experimentally that the vision perception has linear relationship with the saturation parameterC′. This kind of saturation test image has various applications, such as in the checking of color masking effect in visual experiments and the testing of the visual effects of image similarity component.

scholarly journals Measuring color differences in automotive samples with lightness flop: A test of the AUDI2000 color-difference formula

2014 ◽  
Vol 22 (3) ◽  
pp. 3458 ◽  
Author(s):  
Manuel Melgosa ◽  
Juan Martínez-García ◽  
Luis Gómez-Robledo ◽  
Esther Perales ◽  
Francisco M. Martínez-Verdú ◽  
...  
Keyword(s):  
Color Difference ◽  
Difference Formula ◽  
Color Differences

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.

Evaluation of CIELAB-Based Color Difference Formulae Using a Printing Data Set

2010 ◽  
Vol 174 ◽  
pp. 44-47
Author(s):  
Yuan Lin Zheng ◽  
Shi Sheng Zhou ◽  
Lin Lin Zhang ◽  
Yong Hong Qi
Keyword(s):  
Statistical Significance ◽  
Color Difference ◽  
National Standards ◽  
Data Sets ◽  
Printing Industry ◽  
Data Set ◽  
Visual Color ◽  
Difference Formula ◽  
Color Differences ◽  
The Difference

Color difference used to test the quality of printing products is one of the most important factors in the printing industry. Many new color difference formulae such as CIEDE2000, CIEDE94, CMC(l:c) etc were developed to improve the uniformity. In this paper the color difference formulae have been compared throughout their weighting functions SL, SC, and SH to the CIELAB components , , . In order to test which color difference formula has the better performance in the printing industry they are evaluated by our own data sets. First of all, we developed a printing data set for evaluating color difference with psychophysical methods. And the visual color differences of every pairs were obtained. After that the color difference formula mentioned before were evaluated using the data set with the standardized residual sum of squares (STRESS) methods which has better mathematical properties to evaluate the performance of color difference formulae using ΔV and ΔE than PF/3 that cannot indicate the statistical significance of the difference between two color-difference formulae. The result shows that CIEDE2000 and CIE94 color difference formulae are better than CIELAB and CMC. Finally we recommend that the national standards and occupation standards should be updated and CIEDE2000 should be popularized in the printing industry.

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
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