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Hmm. I wonder if converting to HSV first would change the results.
by minikomi 11y ago
Hmm. I wonder if converting to HSV first would change the results.
- bootload 11y agodoes HSV capture colour brightness contrast? I imagine finding the brightest and darkest by looking at the grey scales.
- morpher 11y agoYes. The V in HSV is a greyscale value.
- deleted 11y ago[deleted]
- jacobolus 11y agoHSV is a terrible color model for any human purpose. (To be honest, for any purpose whatsoever, unless it’s required for backwards-compatibility with legacy systems.) HSV, like the RGB model it is a trivial derivative of, has dimensions which are not closely correlated with any color attributes relevant to human perception. Instead, use a model such as CIECAM02, IPT, CIELAB (from the 70s but not too bad), or Munsell (basically a big lookup table, from experiments done in the 40s).
- wingerlang 11y agoI take it HSV is HSB (redirected me on wiki). What's bad with that one? I find that using this one in color pickers is the only one that lets me find the correct tones.
- rspeer 11y agoThe main problems with HSV (HSB): - It thinks #00ff00 (full-intensity green) and #0000ff (full-intensity blue) are the same brightness, when the green will be much, much brighter than the blue to human eyes - A large portion of the hue space is dedicated to nearly-indistinguishable green
- wingerlang 11y agoI see. But as a user that just needs to visually pick colors, I think it is the best one I can use.
- ThomPete 11y agoI am not sure what you are getting at here. The models you propose are not what most if any designers use as the purpose is not to manually select best color combinations (there are other ways to do that) but to approach colors a little more structurally. Whether you calibrate your perception to understand one model or the other doesn't seem to be relevant. I am glad to be taught something I didn't know, but for now it sounds more like a theoretical claim than an actual useful one.
- theoh 11y agoI think the parent was referring to the lack of properties like perceptual uniformity in RGB or HSV colour spaces. Check out the "Advantages" section on this Wikipedia page: https://en.m.wikipedia.org/wiki/Lab_color_space https://en.m.wikipedia.org/wiki/Lab_color_space
- ThomPete 11y agoYou but in this context it seems wrong, but maybe thats just me.
- jacobolus 11y ago> not what most if any designers use This is because tool builders originally created their software tools for graphics workstations of the 1970s (at PARC, NYIT, MIT, etc.) / desktop computers of ~1990 (e.g. Adobe Photoshop), and on such slow hardware it was impractical to use better models. Also, the early tool builders were not color scientists, but computer programmers with an amateur understanding of human vision. It’s inexcusable that designers are still using such poor tools today. Hooray for historical inertia!
- brute 11y agoWhile I support all statements in your post, it misses the point completely. This is not at all about "human perception". It's the opposite. The computer is selecting some colors from the picture that it thinks are representative of the color palette used. When you have a look at the code, the way it is done is that it takes the RGB values as coordinates, randomly selects 3 (or N) clusters, and then caluclates the euclidean distance of all points to their nearest cluster. It continues to randomly select new clusters until it decides that the result doesnt improve anymore at which point it just stops and prints out the coordinates (colors) of the clusters. It should be immediately clear, that selecting another color model, such as HSL or HSV has a direct impact on the calculated euclidean distance, since these color models are not just simple rotations of the rgb cube. Thus it should lead to other (possibly better) results. I am fairly sure that this is what the parent post was suggesting. The color model used to print out the final colors is/could be independent of the one used internally.
- jacobolus 11y agoEuclidean distance in RGB or HSV or whatever is a terrible metric for judging color differences in any context. Not only are they poorly matched to human perception, but these models are also useless from the perspective of judging chemical details of surface pigments, or whatever physical thing someone might care about. But really, since we’re talking about “dominant color”, and “color” is defined with reference to human vision, what we likely care about is the color “clusters” apparent to a human observer. Which means we should work in a color model which accurately represents features relevant to human vision. (The only time anyone should ever care about RGB is when something is going wrong with their physical display or camera, and the technical details of the I/O medium becomes important to study, or if they are writing software to convert colors represented by a better model <-> RGB for input or output.)
- bootload 11y ago"But really, since we’re talking about “dominant color”, and “color” is defined with reference to human vision, what we likely care about is the color “clusters” apparent to a human observer. Which means we should work in a color model which accurately represents features relevant to human vision." That was my interpretation. The colour I'm interested in is the difference between two colours, delta E (dE) somewhere in the dE there is a rule-set that will do what I'm describing. cf http://zschuessler.github.io/DeltaE/learn/ http://zschuessler.github.io/DeltaE/learn/