How many colors can I extract from one image?

You can choose anywhere from 2 to 10 dominant colors per image. A lower count gives you the few colors that define the image at a glance; a higher count captures more subtle secondary tones.

What image formats are supported?

PNG, JPG, and WebP are supported, along with HEIC/HEIF photos from iPhones, which are automatically converted before analysis.

How is 'dominant' determined — is it just the most common single pixel value?

No. The tool uses MMCQ color quantization to group visually similar pixels into clusters, then ranks each cluster by how many of the image's pixels fall into it. This avoids the problem of two nearly-identical shades of the same color splitting a genuinely dominant color's share and hiding its true prominence.

Why don't the hex codes exactly match a specific pixel I sampled with an eyedropper tool?

Quantization returns each color cluster's average, not a single raw pixel — this is intentional and matches how every dominant-color/palette-extraction tool works, since the goal is the representative color of a region of the image, not one arbitrary pixel within it.

Does image size affect the result?

The tool downsamples large images before analysis for speed, since a representative sample of pixels produces the same dominant colors as analyzing every pixel at full resolution, just far faster.

Can I use this to build a website color theme?

Yes — extract the dominant colors from a hero image or brand photo, then copy the hex codes straight into your CSS variables or design tool for a palette that visually matches your source image.

Is there a file size limit?

Uploads are limited to 25 MB, which comfortably covers photos straight from a phone or DSLR camera.

Are my images stored on your servers?

No. Your image is analyzed in memory to extract its color palette and is immediately discarded after the response is sent — nothing is saved to disk.

Extract Dominant Colors — Get a Color Palette from Any Image

Our Extract Dominant Colors tool analyzes any photo or graphic and generates a palette of its most prominent colors, ranked by how much of the image each one covers. Every swatch comes with its hex code, RGB value, and dominance percentage, and can be copied to your clipboard with one click. It's built for designers picking a color scheme from a mood-board photo, developers matching a website's palette to a product image, and anyone who needs the exact colors used in a picture without opening design software.

Quick Answer

Extract Dominant Colors analyzes an uploaded image and returns its most prominent colors as a ranked palette of hex codes, RGB values, and coverage percentages — each swatch is copyable with one click. Free, and results come from real color quantization of the image's pixels, not a rough guess.

Drop an image here or click to upload

PNG, JPG, WebP, or HEIC — up to 25 MB

How to Use the Extract Dominant Colors from Image

1
Click 'Choose File' or drag and drop an image (PNG, JPG, or WebP) into the upload area.
2
Pick how many dominant colors you want extracted, from 2 to 10 swatches.
3
Click 'Extract Colors' and the tool analyzes the image and returns a ranked color palette.
4
Review each swatch's hex code, RGB value, and percentage of the image it covers.
5
Click any swatch's copy button to copy its hex code to your clipboard.

Why Use Extract Dominant Colors from Image?

Picking a color palette by eye from a reference photo is slow and imprecise — a color that looks like '#3B82F6' to your eye might actually render as '#3E86F2' once you drop it into code, creating a subtle but visible mismatch with your source image. This tool solves that by running real color quantization (the same median-cut/MMCQ algorithm behind well-known palette-extraction libraries) against the image's actual pixel data, so the hex codes you copy are the genuine dominant colors, not an eyeballed approximation. This is useful for extracting a brand palette from a logo or product photo, building a website theme around a hero image, matching UI accents to a photograph, or quickly auditing what colors dominate a competitor's marketing image. Because the analysis runs on the real pixel data rather than a manual sample, the results stay accurate even for photos with subtle gradients or many similar shades, where a naive 'sample one pixel' approach would pick a misleading outlier color.

Frequently Asked Questions

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