Color Picker from Image
Sample any pixel from an image, and extract its dominant palette automatically.
The image is decoded and processed by your own browser. It is never uploaded, and no copy of it exists anywhere but this tab, you can confirm that in the DevTools Network tab while you work.
Choose an image to begin.
Features
- Click any pixel to sample its colour
- HEX, RGB and HSL output
- Automatic dominant-colour extraction
- History of recently sampled colours
- The image never leaves your device
How to use it
- Drop in an image.
- Click anywhere on it to sample that pixel.
- Press Extract palette for the dominant colours.
- Click any swatch to copy its hex value.
How the palette is extracted
The dominant colours are found by colour quantisation. Every pixel is sorted into a bucket by rounding its red, green and blue channels to a coarser resolution, this tool uses 32 levels per channel, and the buckets with the most pixels win. It is a simple approach compared to k-means clustering or the median-cut algorithm that GIF encoders use, but it is fast, runs on any image size, and produces sensible results for the purpose.
One deliberate refinement: very dark and very desaturated pixels are down-weighted. Photographs frequently have large areas of near-black shadow or near-white sky that dominate a naive pixel count while telling you nothing useful about the image's character. Filtering them out surfaces the colours a designer would actually pick out.
A caveat about accuracy. What you sample is the pixel value after the browser has decoded the image and applied any colour management. If the file carries an embedded ICC profile, common in photographs from a decent camera, the value you get here may differ slightly from what a colour-managed application like Photoshop reports. For web work the browser's value is the right one, since that is what visitors will see. For print work, sample in software that respects the profile.
Frequently asked questions
Related tools
Further reading
Read the full guide on the 123MiniApps blog.