In a similar manner, this study confirms the importance of certain color pairs over others, as demonstrated in the original study. For instance, when comparing smallest gamut sequence to largest gamut sequence, more impact is made when cyan is printed before magenta. The same is true for yellow before magenta, cyan before violet, orange before yellow and green before cyan.
However, the original study indicated the combination of magenta before violet and yellow before green. When we compare the second-largest gamut to the largest gamut, we can deduce magenta may be more effective when printed after violet. The 0.5 percent change in gamut between the two sequences, however, may indicate these differences are very minute, which correlates with the original findings. It appears to be more important to ensure cyan is printed before violet and magenta together as a set.
The same kind of analysis can be applied to the green/yellow color pair. The original study indicated the impact of yellow before green is greater than that of green before yellow. This study, however, indicates green before yellow, which could explain the larger difference between the smallest gamut and the largest gamut.
Since the sequences calculated for this study originated from drawdowns, it was important to determine the validity of the original drawdowns conducted and examine their variance from real press conditions. In order to do this, the data from specific patches in the color target was collected and analyzed (Figure 4).
Due to the nature of the sequences that were actually printed, data for OM and OY overprints is missing. The overprint data collected (L*a*b*, L*C*h° and opacity) was used to calculate a predicted sequence in the same way sequences were calculated after the drawdown process. In all cases, except for in the case of the cyan/green pair, the overprint data yielded the same sequence, which produced the widest gamut of the printed samples.
Here, the most variation from drawdown to press lies in the green sector. Data from press cyan/green overprints did not yield the same sequence as data from drawdown cyan/green overprints. In addition, while press data indicated YC as the best sequence, it also produced the largest difference in tetrahedron volume from drawdown to press.
Despite these discrepancies, drawdowns may prove an accurate resource for determining optimum EG sequence with only one pressrun to calibrate and determine real gamut size. The average difference between the tetrahedron volume from drawdowns and tetrahedron volume from press data is only 6 percent of the press tetrahedron volume, meaning drawdown data is relatively accurate in determining print sequence. Special attention should be paid to the green sector, but in general placing green in the sequence before its yellow and cyan pairs.
As seen in Figure 3, changing the print sequence of EG inks can result in a 6 percent increase in gamut, meaning the number of Pantone colors producible is increased. But what does a 6 percent gamut increase mean visually, and can the consumer notice a difference? In both the smallest and the largest gamut, 70 percent of the Pantone + Solid Coated library falls within gamut. Furthermore, 79 percent of the library is producible with a Delta E 2000 less than 2.0 in the largest gamut, while 78 percent is producible in the smallest gamut. There are 76 colors that fall in gamut with a Delta E 2000 less than 2.0 in the larger gamut, but are not in gamut in the smallest gamut. Those colors most affected by any change in EG sequence are colors that contain large percentages of orange, green and violet. There are 27 colors that fit this criterion (Figure 5), most of which fall in the orange/red sector.
In order to determine if the consumer can detect a difference when the print sequence is changed, a qualitative survey was conducted using a design which simulated a realistic consumer product. The sample contained a few points that were dependent upon the EG sequence, but remained fairly neutral overall (Figure 6). This choice was made to simulate a product that may have specific brand colors that may have previously required a spot ink, but now can be easily achievable with an optimized EG sequence.
After conducting an initial survey of 150 Clemson students (determined to be a statistically valid sample of the population of 20,000 Clemson students, with 90 percent confidence and 10 percent margin of error), results were examined. Eighty-two students were unable to detect any differences in color. In other words, the true proportion (considering the given 10 percent margin of error) of Clemson student consumers who see a difference is between 35 percent and 55 percent. This leaves the proportion of consumers who do not see a difference between 45 percent and 65 percent. Those students who were able to detect any difference (and who chose one sample over the other) were roughly equally likely to prefer either sample. Thirty-two students said they preferred the sample printed with the smaller gamut, while 24 students said they preferred the sample with the larger gamut. Again, the true proportion of all consumers who prefer the smaller gamut sample can be estimated to be between 11 percent and 31 percent, and the true proportion of all Clemson student consumers who prefer the larger gamut sample can be estimated to be between 6 percent and 26 percent.
Since the beginning sample seen in Figure 6 was a mild application of the capabilities of EG color, a survey was conducted using a design that exaggerated the bounds of EG to see if any differences in observation occurred. The second file represents a more typical product that utilizes EG; it is more colorful and pushes the edges of the producible gamut. Since most of the variable Pantone colors fill in the orange sector, a process image that utilized a number of orange tones was used to exaggerate differences in the color profiles (Figure 7). Due to time constraints, this sample was output on a digital inkjet proofer using the Esko Equinox profiles created earlier in this study.
Using these proofs, another survey was conducted in a similar fashion. The same sample size—150 Clemson students—was surveyed. In the survey conducted using the exaggerated sample, 96 students said they could detect a difference between the two color profiles; 54 students could not. In terms of the true proportion of Clemson student consumers (again, considering the given 10 percent margin of error), 54 percent to 74 percent are able to detect a difference, while 26 percent to 46 percent are not. Of those students who were able to detect a difference and who chose to answer this question, 28 students preferred the wider gamut and 28 students preferred the smaller gamut. So, the population of consumers is equally likely to choose the smaller gamut over the larger gamut, and vice versa.
However, when we take into account the expression of individual observations, we can begin to understand why some consumers have a particular preference: The most common determining factor in preference for these samples was darkness and contrast. If a student perceived one sample as having darker shadows and lighter highlights overall, he or she tended to prefer that sample. However, if the student perceived the sample to be too dark overall, he or she tended to prefer the opposite sample.
Conclusion
As seen in the results of the qualitative survey, a 6.6 percent increase in gamut that can occur when changing and optimizing EG ink sequence may not have a profound effect on the way a consumer sees a package.
However, this study may indicate there are some other areas that need to be explored in addition to optimizing EG sequence. Through this study, drawdowns were determined to be an effective method for estimating real ink sequence, and will save printers makeready time and money by reducing the number of characterization pressruns (reducing the number from two to one).
In addition, optimizing the print sequence allows the printer to save costs on special spot color inks. The qualitative survey shows that while optimizing the sequence doesn’t have a profound effect on the way a consumer views a package, there is some room for more research that may indicate a preference of an EG sequence over conventional CMYK or modified process with spot color. In addition, further research may be done to explore consumer preference of contrast; research into the best placement of black in the sequence seems warranted.
About the Author: Nina Davis is a fourth-year student in the Graphic Communications degree program at Clemson University. Soon after beginning the graphics program, Nina was hired at the Sonoco Institute of Packaging Design and Graphics, where she works as a research assistant. Throughout her course work, she has focused her interests on color management, prepress and packaging. These interests have correlated with her work as an intern at Southern Graphic Systems and with the Clemson Phoenix Challenge team. Over the summer, she completed an internship at Wikoff Color Corp.
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