Monday, April 12, 2010

Color errors in printing

A couple of centuries ago, a gentleman had to diligently practice his fencing to survive. Today a technologist has to diligently practice his google-fu to survive.
Last week I noted in Vanity Publishing how a recent study had shown that for self-publishing and photo-books color accuracy is not an important quality factor. Does this mean we can just forget about color quality and invest our time into something more useful?

Vanity publications are only a small part of the total color printing market, and there are many customers that care a lot about color accuracy. In Silicon Valley's distorted reality field it is easy to get caught up in the hype and think everywhere it is like here. Sure, fresh MBAs turn their thesis on a printing related Web service into a start-up and then hire logistics experts to squeeze out good profits, or at least good investors, and think investing in good press people is a waste of resources, but in the real world there are many highly competent press people who make a decent living while contributing to society.

Therefore, I decided to practice my google-fu to learn what is out there. I could navigate to UGRA, FOGRA, GATF, TAGA, and all the other experts, but I was interested in learning what exists out there in the wild.

There are many competent color printers out there who know what they are doing and do not get confused by ICC profile versions. One who came out on Google's first result page was Ing. Rainer Wagner of WPC. His site is very competent and his data is consisted with my own experience. The fact that he openly shares it is another mark of his competence. So let us have a look at his data on tolerances in spectral color measurement.

tolerances in spectral measurement

The green line denotes the minima in his tolerances, while the maxima are in red. It is good engineering practice to first consider the big problems, then proceed towards the small potatoes (business people tend to go for the low-hanging fruit).

The biggest error source is the provenience of the ICC profiles. Most standards are not about how something should be done; rather, they specify how an output looks so the next entity in the workflow can process it. For example, JPEG does not specify how to encode an image, it specifies how to decode an image. Standard bodies enable to implement in an interoperable way the very best technology, but they never say anything of how the technology is implemented, other than giving examples to get interested parties started. The implementation is where businesses differentiate and compete.

In this spirit, the various providers of ICC profiles, as well as the producers of profiling software, have products at various quality levels so they can compete in every market. If they are interested in the high-end market, they will hire skilled color scientists; if they are just interested in making a buck in the mass-market, they may just hire cheap labor in a low-wage country.

Therefore, a good printer must be knowledgeable on the various sources of ICC profiles. When a job comes in, the printer will look at the embedded profiles to gauge their producer's reputation, then he can assess what quality level is realistic and manage the customer's expectations. If external profiles are specified, the good printer will have good profiles at hand.

Next down is the color difference between a proof printer and a press. This is a tough problem for offset and gravure printing, but in digital printing it is a non-issue, because the press is used for proofing.

I was surprised next on the list is the error introduced by color transformation algorithms in color management modules. I thought that after 25+ years all color transformation problems would have been solved. What happened? If you know, please leave a comment.

It is not a surprise there is no perfect agreement between instruments. Once at a lecture at RIT, Dr. Robert Hunt made the comparison that performing a color measurement is like placing a color chart in the fireplace, view it with a looking glass from the roof though the chimney, while the spouse would illuminate it by shining a flashlight from the garden.

Indeed, designing color measurement apparata is a very difficult art. What is the sphere diameter? Where are the baffles located? How big are they, etc. Measurements can only be compared if they are made with instruments using exactly the same head geometry.

Press drift is another number that surprises me. Online feedback loops based on viscosity measurements and online spectrophotometers should allow very tight tolerances. I am not a press person, so I cannot explain this large tolerance.

Today the drift of a proof printer is very small, and a diligent printer will not have much trouble keeping the drift below the perceptual threshold.

The tolerance for measurements with the same instrument can be made very small. However, it is surprising to see how often things get out of control. The instrument tilt is very critical, as is the diligent calibration. It is not only a matter of the instrument itself, but also of the operator. Therefore, techniques like collaborative testing and periodic absolute calibration are essential for high quality color printing (see here for details).


  1. Interesting post. However, with color, the errors, may not add, but may actually cancel out. So for any given error in, say, the press drift of +4 DE on one vector, some portion maybe canceled out by an error in the profile. Of course, the errors may add. Inspired by your post, I ran a quick Monte Carlo. I assumed flat random distributions. If the errors always add, the range of errors is quite large, in the 10s of DE. However, if you allow that the errors may add or cancel, the distribution is much tighter with a 98% chance of being less than 5 DE.

    This analysis is, of course, worthless because many of the errors listed are systematic rather than random (and my primitive model didn't take in to account the nature of the errors very well). But the point is, while it is good to reduce the large variances, it is also worth looking at the variances that are very difficult to correct, perhaps press variations, and endeavor to reduce the other variances to within the maximum error of the worst case.

    As to the errors in transform, perhaps this is due to non-reversible "errors" that occur in the transforms (like clipping-type gamut mapping). If the analysis was done by running test colors through in one direction and then back, this may appear as "error" in the transform.