Image Color Extractor

How to use Image Color Extractor

1. Choose an image, or drop one onto the page.
2. Read the extracted colours and their share of the image.
3. Copy the hex values you want, then check any text pairing for contrast.
4. Large flat areas dominate the result — crop to the region you care about for a better sample.
5. Values from a JPEG are approximate, because compression shifts pixels near edges.
6. The image is processed in your browser and never uploaded.

How dominant colours are found

The image is drawn to a canvas, sampled pixel by pixel, and the colours are grouped into clusters so that near-identical shades count as one. Without that grouping a photograph returns thousands of distinct values, since a gradient of sky is a different colour in every pixel. The clusters are then ranked by how much of the image they cover, which is why a large flat background usually dominates the result even when it is the least interesting colour in the picture.

What you get is not the designer’s original value

A colour sampled from a JPEG has been through lossy compression, which shifts pixel values especially near edges, and through whatever colour profile the file carries. A logo screenshotted from a website has additionally been through the browser’s rendering and possibly a scaling step. The result is close, and it is not the brand’s specified hex. For brand work, get the value from the guidelines; use extraction for inspiration and for matching to an image you are actually displaying.

Turning extracted colours into a usable palette

The dominant colours of a photograph are rarely a good interface palette on their own — they tend to cluster in lightness and saturation, because that is what makes a photograph look coherent. Take one or two as your accent, then build neutrals separately and check every text pairing for contrast. A palette derived from an image looks harmonious precisely because its colours are close together, which is the opposite of what text readability needs.