The optimization of color-prediction models for colored cotton fiber yarns

2019 ◽  
Vol 89 (19-20) ◽  
pp. 4007-4014 ◽  
Author(s):  
Liu Yang ◽  
Jing Bai ◽  
Ruiyun Zhang ◽  
Yi Ding ◽  
Feng Ji ◽  
...  
Keyword(s):  
Prediction Models ◽  
Color Difference ◽  
Color Measurement ◽  
Target Color ◽  
Color Matching ◽  
Average Color ◽  
Color Differences ◽  
Computer Aided ◽  
Colored Cotton ◽  
Color Prediction

Color matching is necessary in the manufacture of colored fiber yarns, and its accuracy is one of the main goals in computer-aided color matching. A limited number of pre-colored fibers are blended to match the target color through predicted recipes. Of the color-prediction models applied in computer-aided color matching, two common ones, Stearns-Noechel and Friele, were selected to be modified to improve the color-prediction accuracy in this paper. The models were modified in three ways, in which the pending parameters in the models were determined through statistical analysis depending on median, wavelength, and components; thus, the Stearns-Noechel model was modified to Stearns-Noechel 1, Stearns-Noechel 2, and Stearns-Noechel 3, and the Friele model was modified to Friele 1, Friele 2, and Friele 3. The six modified models were affirmed through 261 colored fiber yarns prepared from five primary cotton fibers, including two-, three-, four-, and five-primary blends. The prediction results of 261 samples showed that Stearns-Noechel 3 had the highest accuracy among the modified Stearns-Noechel models, especially for four-primary blends with an average color difference of 0.50 Color Measurement Committee (CMC) (2:1) units, whereas Friele 1 had the highest accuracy among the modified Friele models, especially for five-primary blends with an average color difference of 0.46 CMC (2:1) units. These results indicate the modified model Stearns-Noechel 3 can be used in color prediction when there are fewer than five yarn components, and Friele 1 can be used for five components with lower color differences that better meet color-matching requirements in practical production.

Mathematical Model and Implementation of the Density-Based Gravure Spot-Color Matching

2010 ◽  
Vol 174 ◽  
pp. 56-59 ◽  
Author(s):  
Ru Bai Luo ◽  
Shi Sheng Zhou ◽  
Nan Jiang ◽  
Qiu Juan Yang
Keyword(s):  
Functional Module ◽  
Color Difference ◽  
Target Color ◽  
Color Matching ◽  
C Programming Language ◽  
C Programming ◽  
Color System ◽  
To Come ◽  
Matching Color ◽  
Spot Color

In the paper, the spot-color was divided into ten color areas based on the theory of Munsell color system, then, the model samples in IGT was produced according to each color area. After measuring and analyzing the data of the proofs, Gravure spot-color matching based on masking equation by the means of ten color areas was established. Finally, the paper validated the precision of Gravure spot-color matching model by the method of color difference. The functional module of Gravure spot-color matching in the commercial spot-color matching system was developed using C++ programming language and MySQL Database. The running result of spot-color matching software indicated that the Gravure spot-color matching system based on the proposed method is easy to come true by computer programming, and the color difference between matching color and target color is suitable range (△E≤6 ).

Comparative Study of Ink-Jet Color Proofing Systems Based on Color Management

2014 ◽  
Vol 910 ◽  
pp. 405-409
Author(s):  
Chang Xian Cheng ◽  
Yan Mei Liang
Keyword(s):  
Color Difference ◽  
Management Systems ◽  
Color Management ◽  
Color Matching ◽  
Color Gamut ◽  
Matching Effect ◽  
Ink Jet ◽  
Color Differences ◽  
Jet Printing ◽  
Different Color

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.

scholarly journals Color-Matching and Blending-Effect of Universal Shade Bulk-Fill-Resin-Composite in Resin-Composite-Models and Natural Teeth

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Rasha M. Abdelraouf ◽  
Nour A. Habib
Keyword(s):  
Resin Composite ◽  
Visual Assessment ◽  
Color Difference ◽  
Color Measurement ◽  
Color Matching ◽  
Occlusal Caries ◽  
Close Match ◽  
Visual Scoring ◽  
Composite Models ◽  
Natural Teeth

Objectives. To assess visually color-matching and blending-effect (BE) of a universal shade bulk-fill-resin-composite placed in resin-composite-models with different shades and cavity sizes and in natural teeth (extracted and patients’ teeth).Materials and Methods. Resin-composite-discs (10 mm × 1 mm) were prepared of universal shade composite and resin-composite of shades: A1, A2, A3, A3.5, and A4. Spectrophotometric-color-measurement was performed to calculate color-difference (ΔE) between the universal shade and shaded-resin-composites discs and determine their translucency-parameter (TP). Visual assessment was performed by seven normal-color-vision-observers to determine the color-matching between the universal shade and each shade, under Illuminant D65. Color-matching visual scoring (VS) values were expressed numerically (1–5): 1: mismatch/totally unacceptable, 2: Poor-Match/hardly acceptable, 3: Good-Match/acceptable, 4: Close-Match/small-difference, and 5: Exact-Match/no-color-difference. Occlusal cavities of different sizes were prepared in teeth-like resin-composite-models with shades A1, A2, A3, A3.5, and A4. The cavities were filled by the universal shade composite. The same scale was used to score color-matching between the fillings and composite-models. BE was calculated as difference in mean-visual-scores in models and that of discs. Extracted teeth with two different class I-cavity sizes as well as ten patients’ lower posterior molars with occlusal caries were prepared, filled by universal shade composite, and assessed similarly.Results. In models, the universal shade composite showed close matching in the different cavity sizes and surrounding shades (4≤VS<5) (BE = 0.6–2.9 in small cavities and 0.5–2.8 in large cavities). In extracted teeth, there was good-to-close color-matching (VS = 3.7–4.4 in small cavities, BE = 2.5–3.2) (VS = 3–3.5, BE = 1.8–2.3 in large cavities). In patients’ molars, the universal shade composite showed good-matching (VS = 3–3.3, BE = −0.9–2.1).Conclusions. Color-matching of universal shade resin-composite was satisfactory rather than perfect in patients’ teeth.

Masking Ability of IPS e.max ALL-Ceramics System of HO Series

2012 ◽  
Vol 512-515 ◽  
pp. 1784-1787
Author(s):  
Shan Yu Zhou ◽  
Long Quan Shao ◽  
Lin Lin Wang ◽  
Yuan Fu Yi ◽  
Bin Deng ◽  
...  
Keyword(s):  
Color Difference ◽  
Metal Substrate ◽  
The Other ◽  
Target Color ◽  
White Background ◽  
Color Match ◽  
Dark Background ◽  
Color Differences

To evaluate the masking ability of IPS e.max all-ceramics system of HO series. IPS e.max Press HO ingots were fabricated into twenty cylindrical specimens (n=5) with the diameter of 13mm and four different thinknesses (0.4mm, 0.6mm, 0.8mm, 1.0mm). All specimens after veneered, gazed and cemented to metal substrate disks (thickness 3mm, diameter 13mm) were measured on both the white background and metal substrate disks background using a spectrophotometer and values of L, a and b were calculated to compare color differences among four groups. Meanwhile ΔE with the preselected required color (A2 color) were calculated. ΔE<1.5 was considered a clinically acceptable color match. In the 0.4mm thickness specimens group, the values of L, a and b significantly increased (-1.36±0.05, -0.15±0.06, -1.46±0.02, respectively) between the white background and abutment background. But there were no significant color differences in the other three groups (P<0.05). In the 0.6mm and 0.8mm thicknesses specimens groups, the color difference values (0.71±0.04, 1.14±0.06, respectively) with A2 color were less than the defined value. Thus the cylindrical specimens with the thickness of 0.6mm, 0.8mm and 1.0mm could mask the metal substrate disks background sufficiently and the thickness of 0.6mm and 0.8mm had an acceptable color match compared with the target color. IPS e.max all-ceramics system of HO series can produce clinically acceptable color match and have the capacity to mask a dark background such as a dark tooth or core buildup material.

Spectrophotometric color matching for pre-colored fiber blends based on a hybrid of least squares and grid search method

2021 ◽  
pp. 004051752198978
Author(s):  
Ge Zhang ◽  
Ruru Pan ◽  
Jian Zhou ◽  
Lei Wang ◽  
Weidong Gao
Keyword(s):  
Least Squares ◽  
Production Efficiency ◽  
Least Squares Method ◽  
Color Difference ◽  
Search Method ◽  
Grid Search ◽  
Color Matching ◽  
Standard Samples ◽  
Grid Search Method ◽  
Colored Cotton

Computer color matching can improve production efficiency and reduce costs in color spun. However, in practice the computer color matching success rate for pre-colored fiber blends has not been good, leading to customers being unsatisfied with the accuracy of the color matching results. Aiming to improve the accuracy, a hybrid of least squares and grid search method has been proposed for spectrophotometric color matching of pre-colored fiber blend based on the improved Kubelka–Munk (K-M) double-constant theory. Two-primary, three-primary, four-primary, and five-primary pre-colored cotton fiber blends were prepared as standard samples to evaluate the color matching accuracy of the proposed method. Compared with the least squares method and the grid search method, the proposed method achieved better color matching effects and greatly shortened the calculation time, respectively. For 42 pre-colored fiber blends, the average color difference between the predicted results obtained by the proposed method, least squares method, and grid search method and the spectrophotometer measurements were respectively 0.29, 0.53, and 0.36 CIE2000 units. The experimental results indicated that the proposed method could predict the formulation of standard samples quickly and effectively, and that it was superior to other methods in providing satisfactory color matching results for the enterprises.

The Performance of Computerized Spectrum Color Matching Based on Kubelka-Munk Theory and its Color Rendering on Offset Ink Sets

2010 ◽  
Vol 174 ◽  
pp. 72-76 ◽  
Author(s):  
Yuh Chang Wei ◽  
Wen Min Chou ◽  
Chih Lang Chen
Keyword(s):  
Color Difference ◽  
Fine Tuning ◽  
Target Color ◽  
Index Test ◽  
Color Matching ◽  
Curve Fit ◽  
Depth Analysis ◽  
Predicted Values ◽  
Fit Index ◽  
Color Rendering

The purpose of the study intended to examine the performance of color rendering based on a computerized spectrum color matching (CSCM) method derived from the Kubelka-Munk theory. In the study, we prepared 2 offset ink sets to produce 30 standard color samples sets. The target color samples were measured by spectrophotometer to compare with the predicted values calculated by the CSCM model. The results showed that average measured color difference (∆E) via CIE L*a*b* and CIE DE2000 formulas between samples and CSCM predicted values averaged 5.89, 3.72 (∆Es), 6.94, 4.22(∆Epv), respectively. The measurements were fallen out the acceptable range of the tolerance of the industrial printing standards. The verification of CFI (Curve Fit Index) test came out with the same conclusion. As a result, we found that the computerized color matching formula derived from Kubelka-Munk theory still required further fine-tuning and more in-depth analysis. In addition, the reflectance database of the ink sets was another important factor affecting the performance of computer color matching model for precise colors prediction.

scholarly journals Color spectra algorithm of hyperspectral wood dyeing using particle swarm optimization

2020 ◽  
Author(s):  
Machao Wu ◽  
Xuemei Guan ◽  
Wenfeng Li ◽  
Qinglong Huang
Keyword(s):  
Particle Swarm ◽  
Color Difference ◽  
Particle Swarm Algorithm ◽  
Model Parameters ◽  
Color Matching ◽  
Evaluation Standard ◽  
Color Differences ◽  
Fixed Parameter ◽  
Particle Swarm Method ◽  
Parameter Values

Abstract To improve the accuracy and practicality of the intelligent color-matching application of wood dyeing technology, Fraxinus mandshurica veneer was selected as the dyeing material. First, based on the Friele model and Stearns–Noechel model, the model parameters were cyclically assigned to calculate the optimal fixed parameter values and predictions. Then, particle swarm algorithm was used to optimize two algorithm models, the obtained reflectance curve was fit, and the color differences were calculated according to the human eye-based CIEDE2000 color difference evaluation standard formula. Last, the two formulas to predict the color difference and spectral reflectance were compared. First, the two optimization algorithms were compared according to the size of the fitted color difference value, and then, the most accurate optimization algorithm was selected. When the model parameters were fixed, the average fitted color difference was 0.8202. After optimizing the Friele model, the average fitted color difference was 0.7287, and after optimizing the Stearns–Noechel model, the average fitted color difference was 0.6482. It was concluded that the improved Stearns–Noechel model based on particle swarm method was more accurate than the Friele model for wood color matching.

Color prediction model for hybrid multifilament fabric

2021 ◽  
pp. 004051752110471
Author(s):  
Yujuan Wang ◽  
Wengang Li ◽  
Jun Wang
Keyword(s):  
Pearson Correlation ◽  
Color Difference ◽  
Color Measurement ◽  
Gray Histogram ◽  
Fabric Structure ◽  
Calculation Results ◽  
Iteration Model ◽  
Color Prediction ◽  
Fabric Surface ◽  
The Relationship

In order to facilitate the design of a hybrid filament before spinning, a k-m (Kubelka-Munk) iteration model was proposed, which was based on the calculation method for reflectance of a translucent object and needed to be used in conjunction with a fabric model that can reflect the arrangement order of monofilaments. Therefore, the model can not only calculate the color of each point on the fabric surface, but also the mixed color of the fabric. Twenty fabrics with five different blending ratios of black monofilaments and white monofilaments, four multifilament fineness and three fabric weave types were woven. The relationship between the gray distribution of all points on the fabric surface captured by the camera in a DigiEye colorimeter and calculated by the k-m iteration model was analyzed, and the color difference between the mixed color of the fabric tested by the Datacolor spectrophotometer and that calculated by the k-m iteration model was calculated. The results show that the intersection distance and Pearson correlation coefficient between the gray histogram of the photographed fabric image and that of the calculated fabric image were 0.79 and 0.89, respectively. The average color difference obtained by the k-m iteration model was 0.92 Color Measurement Committee (2:1) units, which was best compared with the calculation results of other models. By discussing the fabric structure parameters causing the lightness difference, it was concluded that the calculated lightness was smaller than the measured lightness difference for fabric with a longer float length, smaller multifilament fineness and a larger black monofilament blending ratio.

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.

scholarly journals Effect of Diet on Bloom Time of Beef

2019 ◽  
Vol 3 (2) ◽  
Author(s):  
K. Insausti ◽  
M. J. Colle ◽  
P. D. Bass ◽  
I. Goenaga ◽  
O. Urrutia ◽  
...  
Keyword(s):  
High Energy ◽  
Color Measurement ◽  
Post Mortem ◽  
Northern Spain ◽  
Longissimus Dorsi Muscle ◽  
European Guidelines ◽  
Color Differences ◽  
Typical Period ◽  
H 26 ◽  
The Moment

ObjectivesThe objective of the study was to assess the evolution of the bloom color in beef aged for 8 d to establish the moment of measurement in which values of L*, a* and b* stabilize and are representative of the characteristic color of the meat from beef fed different diets.Materials and MethodsIn the current study, eight young Pirenaica bulls were used. The bulls were born and reared on a private commercial Protected Denomination Origin (PDO)-approved farm located in the region of Navarra (Northern Spain). After weaning at approximately 4 mo of age, the calves were administered the same diet until month 12. The bulls were separated in two groups and each of group was fed a different energy level diet (High energy, H: 2914.2 kcal/kg vs. Low energy, L: 2548.4kcal/kg) until slaughter at 18 mo of age. Diet was based on barley (H: 26% vs. L: 22%), corn (H: 50% vs. L: 45%) and soja (H: 17% and L: 17%). The research was conducted under the highest standards of humane care and use of animals in accordance with European guidelines (EU). Longissimus dorsi muscle was removed after 24 h. post-mortem from the left side of the carcasses, pH was measured, and the meat was transported to the Meat Science Laboratory at the Public University of Navarra (Pamplona, Spain) under refrigeration. Steaks were aged in vacuum for 8 d post-mortem, which is the typical period for this type of meat under the PDO Ternera de Navarra. After aging, L*, a*, and b*were recorded every 3 min (5 repetitions per sample) for 102 min with a Minolta CM 2002 Spectrophotocolorimeter. Data were analyzed using the Linear General Model procedure with the IBM SPSS Statistics 24, and significance was determined at P < 0.05.ResultsThe pH values were 5.56 (H) and 5.50 (L) (P < 0.05) thus, no DFD meat was observed. Color differed depending on diet (L*H: 28.88 vs. L*L: 34.26, P < 0.01; a*H: 26.33 vs. a*L: 18.11, P < 0.001; b*H: 11.58 vs. b*L: 7.94, P < 0.001) even if the initial pigment content was not statistically different (H: 5.34 mg/g vs. L: 4.74 g/g; P = 0.107). In fact, beef from the H diet showed higher a* and b* values, and lower L* values than beef from the L diet (P < 0.05). Nonetheless, the time of stabilization for a practical color measurement did not differ between diets.ConclusionIn conclusion, despite the effect of diet on the initial beef color differences, the results of the current study showed that 15 min of meat exposure to oxygen is the minimum in either cases prior to taking measurements of color on beef aged 8 d.

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