Extract Colors from Image
Upload a photo, get the dominant colors as a palette. Part of AI color system tool.
Quick answer: Color extraction analyzes the pixels in an image to identify its most dominant colors. Algorithms like k-means clustering group similar pixels together.
How it works
Upload an image
Drag a photo, screenshot, or artwork onto the upload area.
View extracted colors
The 5 most dominant colors appear as swatches.
Copy what you need
Click any swatch to copy its hex code.
What is color extraction from images?
Color extraction analyzes the pixels in an image to identify its most dominant colors. Algorithms like k-means clustering group similar pixels together and return the centroid of each cluster as a representative color.
This is useful for deriving brand palettes from photography, matching UI colors to product images, or extracting a cohesive palette from inspiration artwork. The extracted colors often need refinement: raw pixel colors may not have sufficient contrast or fit within an accessible color system.
Professional workflows typically extract colors as a starting point, then adjust lightness and saturation to meet design system requirements. A raw photo palette rarely passes WCAG contrast checks without modification.
Run the extracted swatches through the WCAG contrast checker to find the failing pairs, build production-ready ramps with the generate 50 to 950 shade scales, or upgrade to Paletta Pro to lift the whole image into a full design system.
Common use cases
Reverse-engineer inspiration
Pull the dominant colors out of a moodboard image and start a palette from real reference.
Pitch from a hero image
Match the color story of a campaign visual without manually eyedropping each region.
Auto-generate a brand starter
Drop a logo render and get a 5-swatch starting point for the rest of the system. Translate each swatch with the hex to RGB converter so the values land cleanly in code.
Match product photography
Anchor a UI palette to actual product colors so marketing and app stay coherent.
FAQ
Frequently asked questions
The tool runs k-means clustering on the pixels in your image and returns the cluster centroids. Each centroid is a color that summarizes a group of similar pixels, which is why the output tends to match the dominant tones a human eye picks up rather than the raw most-frequent pixel.
The free tool extracts five colors, which is the size most designers reach for when building a quick mood palette. Five clusters are enough to capture the dominant hues of most photographs without producing near-duplicates.
Resolution does not matter much because the algorithm samples pixels rather than reading every one. JPEG compression artifacts and heavy filters can shift hues, so a clean source image gives more faithful results. Photos in soft natural light tend to extract more usable palettes than hard flash.
Copy any hex from the extracted palette into Paletta Studio to keep working with it, generate accessible shade scales, and check contrast. Paletta Pro adds a Library where extracted palettes are saved across sessions and synced to the Figma plugin.
Extracted colors are a starting point.
The Paletta Figma plugin turns them into shade scales and Figma Variables, with contrast checked, inside the file you are already working in.