# Computing Image Similarity based on Color Distribution

## Image Similarity based on Color Palette Distribution

I am trying to compute similarity between two images based on their color palette distribution, let's say I have two sets of key value pairs as follows,

Img1: {'Brown': 14, 'White': 13, 'Black': 40, 'Gray': 31}

Img2: {'Pink': 82, 'Brown': 8, 'White': 7}

Where the numbers denote the % of that color present in the image. What would be the best way to compute similarity on a scale of 0-100 between the two images?

• There are basically 2 possible ways to go. Simple one is to simply compare colour histograms. This question give pretty good description of several good measures/methods. But if you are going to use it in image search engine or something like that, it makes sense to also mimic human perception of colours, which is much harder task. This paper provides some cues for better human-aware comparison. – ffriend Jul 27 '14 at 22:18
• That's a perfectly adequate answer, @ffriend. – Emre Jul 28 '14 at 1:27
• This is a cross post from Cross Validated. Anyone know what to do? – JenSCDC Jul 28 '14 at 2:23
• @ffriend: Please post your comment as an answer so it can be accepted. – Nitesh Nov 25 '14 at 17:29

 H1 = [ 14, 13, 40, 31 ]; -- histogram #1 (first image)