Extract Colors from an Image (Dominant Color Extractor)

Upload an image to automatically extract its dominant colors — the representative colors used in a photo or illustration. All processing happens entirely in your browser; the image is never sent to a server.

Usage Tips

  • Click the copy button below each swatch to copy its HEX code to the clipboard — ready to paste directly into CSS or your design tool.
  • Choose 4, 8, or 12 colors to extract. Pick 4 for a simple logo palette, or 12 to capture the subtle variations in a detailed photo.
  • Transparent areas in PNG images are automatically excluded, so the extracted colors focus on the actual subject rather than the background.
  • All processing runs locally in your browser using the Canvas API — the image itself is never sent to any server, so it's safe to use with sensitive images.
  • Colors are listed from most to least frequent. The colors shown first occupy the largest area in the image.

Frequently Asked Questions

This tool uses a simple algorithm that quantizes the image into coarse color buckets and returns the average color of the most frequent bucket as the representative color. It's good enough for getting a quick sense of an image's overall color tones, but keep in mind it isn't as precise as more rigorous clustering methods (like k-means) used in professional color palette tools.

No. This tool uses the Canvas API to load the image and extract colors entirely within your browser (client-side). The image data is never sent to a server, so it's safe to use even with sensitive images.

Any common image format that a browser's tag can display — including JPEG, PNG, WebP, and GIF — should work, matching whatever formats your browser's file picker accepts for images.

Yes. Each color is shown as a HEX code (e.g. #3366cc) that you can copy to the clipboard with one click, so you can paste it directly into Figma, Photoshop, CSS, or any other tool that accepts HEX color values.
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Side Note — The work of finding brand colors from photos

Extracting the colors used in a photo or product package is a routine task in web and graphic design work. When building a brand's visual guidelines, designers often start by pulling representative colors out of existing photos or logos, then use those as candidates for a corporate or accent color. What used to be done by eye with an eyedropper tool, one color at a time, can now be automated with algorithms like the dominant color extraction used here.

There are many algorithms for color extraction. The bucket-quantization-and-frequency approach used by this tool rounds each pixel's RGB value into a coarse group and counts how often each group appears — a simple technique that's cheap to compute and runs fast. More advanced approaches, such as k-means clustering, group colors based on distance in color space and can produce more natural-looking groupings, at the cost of heavier computation.

One interesting quirk is how differently the same image can look depending on how many colors you extract. Pulling just 4 colors reveals the broad tone of an image — whether it leans warm or cool — while extracting 12 starts to pick up subtle variations from shadows and reflected light. Adjusting the count lets you pull different levels of detail out of the very same image.

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