8 ms·

Extracting Colors With Colorific

97 points by dhotson 14y ago

blvr 14y ago
For problem 3: Why exclude all greys? If you asked me what colour that logo was I'd say black/red/white/grey, not red/dark red.
- tinco 14y ago
  This was my first question too. In that picture, not any grey would match with the reds to give the feel of that image.. probably.. Maybe just order by saturation, and then limit to 5 colors?
- dhotson 14y ago
  Yep, you're right. It's difficult to differentiate greys that are important vs those that we don't care about. Our current solution works not too badly and gives us results that are more visually appealing, but I agree we could do better. I'd like to try ranking greys lower somehow.. maybe some kind of weighting by saturation could help.
SkyMarshal 14y ago
Very awesome. Google's logo has 255 colors (including shades). With most other companies I might consider that to be a coincidence.
- chime 14y ago
  255 is not because Google designers chose 255 specific shades but rather the limitation of 8-bit GIF color palette.
  - joshu 14y ago
    https://www.google.com/images/srpr/logo3w.png https://www.google.com/images/srpr/logo3w.png
    - flixic 14y ago
      256 (not 255) color palette also applies to 8-bit PNGs.
trun 14y ago
This is really neat. One of my favorite Windows design features (there aren't many) is the way icons in the taskbar are highlighted with their primary color when you mouseover. This seems like the perfect solution to replicate that effect elsewhere.
- EtienneK 14y ago
  I noticed the other day that Ubuntu's Unity also does this. It's a very nice feature.
callmeed 14y ago
I'd like to find or make a ruby version of this.
- rockmananoff 14y ago
  If you do, reply here. I'd like one too.
- dsucher 14y ago
  Are you actually working on this? Because if not, I'm tempted! Just don't want to duplicate effort here.
ZenPsycho 14y ago
It would be nice if there was some acknowledgement of previous work in this area like the median cut algorithm http://en.wikipedia.org/wiki/Median_cut http://en.wikipedia.org/wiki/Median_cut the neuquant algorithm http://members.ozemail.com.au/~dekker/NEUQUANT.HTML http://members.ozemail.com.au/~dekker/NEUQUANT.HTML or the dozens of other image to palette services a google search away (including one that google uses itself for image search) So, maybe an explanation of why this is better than those, different from those, a comparison of sorts. Or would it be better if some third party did this "benchmarking" work eh? specifically, I am concerned that this approach is based on tiny micro-heuristics based on specific images and not a robust statistical model of human perception. edit: here's another (I may use this comment to continue collecting existing algorithms) http://www.springerlink.com/content/f002412013877333/ http://www.springerlink.com/content/f002412013877333/
- dhotson 14y ago
  We haven't really looked too deeply into existing research in this area, so I'm not sure how our approach compares. We'd still be very interested if you've got any suggestions for material to check out. One difference between our program and other general purpose quantization algorithms is that we wanted to optimise for logo designs and images with flat shapes and colors (as opposed to photos with millions of colors). We also wanted to get something working quickly so that we could get onto some large scale color analysis stuff (which we'll hopefully be writing about soon). There's definitely room for improvement in the color extraction process.
  - ZenPsycho 14y ago
    One thing I would like to research is the fact that once you map colors into lab space you end up with a point cloud with clusters around the primary colors. the problem then becomes using AI techniques to find the "peaks" in this data, and finding how the results from that step statistically match up to human perception of primary colors. This ends up being a similar problem to signal processing the output from a capacitive touch screen. The processor at a low level simply receives a 2D capacitance image from which it must extract the center points of fingers and their sizes- And there is a broad range of literature to find on this more generalized problem of "peak detection".
johnx123-up 14y ago
How is this different from ImageMagick? http://valokuva.org/?p=72 http://valokuva.org/?p=72 (really asking)
philjackson 14y ago
$ echo myimage.png | colorific Seems a slightly odd way to get filenames.
- dhotson 14y ago
  It's because we're running this over millions of images. We don't want to pay the startup cost each time.

97 points by dhotson 14y ago

blvr 14y ago

For problem 3: Why exclude all greys? If you asked me what colour that logo was I'd say black/red/white/grey, not red/dark red.

tinco 14y ago
This was my first question too. In that picture, not any grey would match with the reds to give the feel of that image.. probably.. Maybe just order by saturation, and then limit to 5 colors?
dhotson 14y ago
Yep, you're right. It's difficult to differentiate greys that are important vs those that we don't care about. Our current solution works not too badly and gives us results that are more visually appealing, but I agree we could do better. I'd like to try ranking greys lower somehow.. maybe some kind of weighting by saturation could help.

SkyMarshal 14y ago

Very awesome. Google's logo has 255 colors (including shades). With most other companies I might consider that to be a coincidence.

chime 14y ago
255 is not because Google designers chose 255 specific shades but rather the limitation of 8-bit GIF color palette.
- joshu 14y ago
  https://www.google.com/images/srpr/logo3w.png https://www.google.com/images/srpr/logo3w.png
  - flixic 14y ago
    256 (not 255) color palette also applies to 8-bit PNGs.

trun 14y ago

This is really neat. One of my favorite Windows design features (there aren't many) is the way icons in the taskbar are highlighted with their primary color when you mouseover. This seems like the perfect solution to replicate that effect elsewhere.

EtienneK 14y ago
I noticed the other day that Ubuntu's Unity also does this. It's a very nice feature.

callmeed 14y ago

I'd like to find or make a ruby version of this.

rockmananoff 14y ago
If you do, reply here. I'd like one too.
dsucher 14y ago
Are you actually working on this? Because if not, I'm tempted! Just don't want to duplicate effort here.

ZenPsycho 14y ago

It would be nice if there was some acknowledgement of previous work in this area like the median cut algorithm http://en.wikipedia.org/wiki/Median_cut http://en.wikipedia.org/wiki/Median_cut the neuquant algorithm http://members.ozemail.com.au/~dekker/NEUQUANT.HTML http://members.ozemail.com.au/~dekker/NEUQUANT.HTML or the dozens of other image to palette services a google search away (including one that google uses itself for image search) So, maybe an explanation of why this is better than those, different from those, a comparison of sorts. Or would it be better if some third party did this "benchmarking" work eh? specifically, I am concerned that this approach is based on tiny micro-heuristics based on specific images and not a robust statistical model of human perception. edit: here's another (I may use this comment to continue collecting existing algorithms) http://www.springerlink.com/content/f002412013877333/ http://www.springerlink.com/content/f002412013877333/

dhotson 14y ago
We haven't really looked too deeply into existing research in this area, so I'm not sure how our approach compares. We'd still be very interested if you've got any suggestions for material to check out. One difference between our program and other general purpose quantization algorithms is that we wanted to optimise for logo designs and images with flat shapes and colors (as opposed to photos with millions of colors). We also wanted to get something working quickly so that we could get onto some large scale color analysis stuff (which we'll hopefully be writing about soon). There's definitely room for improvement in the color extraction process.
- ZenPsycho 14y ago
  One thing I would like to research is the fact that once you map colors into lab space you end up with a point cloud with clusters around the primary colors. the problem then becomes using AI techniques to find the "peaks" in this data, and finding how the results from that step statistically match up to human perception of primary colors. This ends up being a similar problem to signal processing the output from a capacitive touch screen. The processor at a low level simply receives a 2D capacitance image from which it must extract the center points of fingers and their sizes- And there is a broad range of literature to find on this more generalized problem of "peak detection".

johnx123-up 14y ago

How is this different from ImageMagick? http://valokuva.org/?p=72 http://valokuva.org/?p=72 (really asking)

philjackson 14y ago

$ echo myimage.png | colorific Seems a slightly odd way to get filenames.

dhotson 14y ago
It's because we're running this over millions of images. We don't want to pay the startup cost each time.