Hue Shift on Tint

I’d like to build on what I’ve written in the previous blog posts about mixing colors more efficiently by identifying the hue of the intended color and then using an understanding of hue shift on neutralization of colors to trace the nearest tube color that can be used to match. There is a two-fold intent here:

  1. To establish a more systematic approach to understanding hue shift.
    • Is it true that neutralizing colors always shifts the hue towards the relatively cooler side of the color wheel? For example, neutralize yellow, and it looks greenish, not orangy.
  2. To provide an efficient color mixing process that artists can use to expedite painting, and spend less time mixing.
    • Painting time is precious, and unless the goal is just to mix colors, most artists will prefer to mix and lay down usable color quickly. Think here of the paintings of Sorolla or Sargent. Their color ‘matching’ may not be photographic or hyper-realist, but it is appealing and so effective that we consider them ideal. The way they were painted is the way they should have been painted. Too many of us get stuck on color matching and miss the dynamic action-response nature of painting that is a distinguishing characteristic of the medium. A robot can be programmed to observe, mix color and ‘print’ with paint according to the Munsell color system.

Here’s the ‘hue-shift’ hypothesis:

When a given color is mixed with a neutral grey of any value, the hue will shift towards the cooler neighboring color on the color wheel.

How do we test this hypothesis?

Plotting with computer scans

The simple way is to take a range of tube colors and tint/shade them to pre-determined values, and then read the colors of each with a digital color reader or scanner. The computer’s HSL reading will provide Hue numbers for each, and these can be plotted to show the hue shift. One person can do this, and I encourage readers to attempt it. All you need is patience, colors, white boards for the colors and a scanner. You can get the HSL values via the color picker. The end results might be plotted on a spreadsheet that, for each tube color, has the Value number (how light or dark it is) as rows, and the Hue number as columns. The Saturation number can be input into the cells for the colors measured. This will give the hue-shift profile for each tube color. Depending on how many values are recorded, we can potentially see a vector or curve of the hue-shift for that specific tube color.

One person can do this, and I encourage readers to attempt it. All you need is patience, colors, white boards for the colors and a scanner. You can get the HSL values via the color picker. The end results might be plotted on a spreadsheet that, for each tube color, has the Value number (how light or dark it is) as rows, and the Hue number as columns. The Saturation number can be input into the cells for the colors measured. This will give the hue-shift profile for each tube color. Depending on how many values are recorded, we can potentially see a vector or curve of the hue-shift for that specific tube color.

The end results might be plotted on a spreadsheet that, for each tube color, has the Value number (how light or dark it is) as rows, and the Hue number as columns. The Saturation number can be input into the cells for the colors measured. This will give the hue-shift profile for each tube color. Depending on how many values are recorded, we can potentially see a vector or curve of the hue-shift for that specific tube color. (In a future post I’ll submit an example chart.)

Note that while the same color swatches may scan differently in different scanners, as long as all the results are done with the same scanner we should get a reasonably accurate set of results. Monitor calibration does not factor in because we’re using the computer’s color picker to determine the HSL number for each. Note that due to pixelation, for any given swatch a few measures should be taken and the mean selected.

However, ‘objective’ computer color is not the same as perceived color. So here’s a subjective approach.

Plotting with user color matching

  • Preparation¬†
    • Take a set of tube colors that align with the primaries and secondaries on the color wheel.
    • For each, neutralize so that there is a light, medium and dark version. To avoid extreme desaturation, we don’t want to mix very light or very dark versions. On a scale of 1-10, perhaps a 7, 5 and 3 would suffice (but this can be modified during the experiment).
    • Put each of these individual colors on a color swatch, numbering them on the back with random numbers that are indexed to the tube colors on a chart the test users don’t have access to (so they can’t look at the numbers and correlate which swatches came from which tube color).
    • Set up a wall chart with the color spectrum in a horizontal grid, with chromatic hues in the middle, and lighter versions of the same hue above them, and darker versions below. Note that for each column the tints and shades of the same hue as the core chromatic color. These will have to be verified with a digital color reader to ensure that hue-shift isn’t skewing the chart itself.
    • Index each color on the chart with a number – it could be the Munsell number or something else that is easy to reference.
  • Validation
    • One at a time, give each¬†user a set of colors across the spectrum (the count should be determined by how long the user can provide focused matching).
      • To get a good sample, ensure that in the end, all the swatches have been given at least three times to users.
    • Have the users match each of their swatches to a cell on the wall chart, and note the number of the cell matched.
    • Plot all user selections on a spreadsheet (see above) to determine hue shift for each tube color.

It would be interesting to have multiple instances of both types of experiments using a broad range of tube colors, and to bring the results together into a public knowledge base. The end result would be information of hue-shift for tube colors that artists can then use to mix colors faster. It can also help us rank tube colors in terms of how broad their hue mixing potentials are. How exactly would this work? Here’s a scenario.

Practical Application

  1. When starting a painting, the painter selects tube colors they want to use.
    • The artist might have preferred colors, or alternatively
    • A more sophisticated (future) color recognition software can propose tube colors based on the color profile of the image.
  2. The artist becomes familiar with the hue shift of each tube color.
  3. To match color:
    • For the beginner, the artist uses a Munsell color swatch to identify the target color, then uses the hue-shift chart to identify the tube color that will produce the closest match.
    • The advanced artist makes a mental note of the desired color, and from knowledge of the hue-shift charts for her palette, picks the corresponding tube color.

Conclusion

In publishing my Hue-shift based methodology for color matching, I’m ‘open-sourcing’ the idea so that the community can pick up on it and perhaps together we can be systematic about collecting this data. Software engineers may someday pick on this and create color-detection to tube color technology to expedite the process for the painter. Imagine you’re out in the field painting en Plein Air and you’re having trouble determining how to mix a color. Having the Zuniga hue-shift charts on hand can help. Alternatively, imagine a phone application lets you take a picture, zoom and select the problematic spot. Since you input the tube colors in your kit, it will tell you which color is the fastest path to obtaining the desired hue at the desired value.

— Roy Zuniga
Langley, WA

 

Copyright (c) 2017 Roy Zuniga

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