Dominant Color Extractor
Automatically extract the most dominant and representative colours from any image. Upload a photo, illustration, or screenshot and get a complete colour palette — the top 5, 8, or 12 colours sorted by frequency. Each colour is shown with its HEX, RGB, and HSL values ready to copy. Perfect for building design systems from brand photos, creating harmonious colour palettes, and analysing image colour composition.
How to Use Dominant Color Extractor
- 1
Upload your image
Click the upload area or drag and drop a JPG, PNG, or WebP image. The extraction works on photographs, illustrations, logos, and screenshots.
- 2
Choose palette size
Select how many colours to extract: 5 (main palette), 8 (extended), or 12 (full detail). More colours capture subtle variations; fewer colours give a cleaner, more usable palette.
- 3
Extract colours
Click Extract. The tool analyses every pixel using a colour quantisation algorithm (median cut or k-means clustering) to find the most representative colour groups.
- 4
Copy colour values
Click any colour swatch to copy its HEX value. Click the colour name to cycle through HEX, RGB, and HSL formats. Export the full palette as CSS variables, JSON, or a colour swatch image.
When to Use This Tool
Quick Reference
About Dominant Color Extractor
The Dominant Color Extractor analyzes any image and identifies the most prominent colors, returning a sorted color palette with hex codes, RGB values, and percentage distribution. This is invaluable for designers who need to match brand colors from a logo image, developers building color-adaptive UIs, and content creators who want a consistent color scheme across their visuals.
Common use cases include:
- Extracting a brand color palette from a company logo to use in design work
- Finding the dominant colors in a product photo to use as background or accent colors in listings
- Building adaptive UI color schemes that match uploaded user photos
- Identifying color trends across a collection of images for marketing analysis
- Matching paint, fabric, or print colors by extracting hex codes from reference photos
Color extraction uses a k-means clustering algorithm applied to the pixel data of the image. The image is first downsampled to a manageable resolution (typically 200×200px) to make the clustering computationally efficient. Each pixel's RGB values are treated as a point in 3D color space. The k-means algorithm partitions these points into k clusters (typically 5–8) by iteratively minimizing the distance between each pixel and its nearest cluster centroid. The final centroid positions represent the dominant colors, and the cluster sizes determine the percentage distribution.
Input formats: JPG, PNG, WebP, BMP, GIF. Output: color swatches with hex codes, RGB values, HSL values, and percentage of image covered. Palette size: 5 to 12 dominant colors. Clipboard copy: click any swatch to copy the hex code instantly.
The entire color extraction algorithm runs in your browser using JavaScript and the HTML5 Canvas API. No image data leaves your device. This makes the tool safe for analyzing proprietary product images, confidential design files, or sensitive photography. For related color work, try the Image Color Picker to sample specific pixels.
Pro Tips for Dominant Color Extractor
For brand color extraction from logos, use a version of the logo on a white or transparent background — background pixels skew the clustering toward white/neutral tones.
The percentage shown next to each color tells you how much of the image it covers — use the top 1–2 colors for backgrounds and the others as accent colors in your design.
When building a UI color scheme from a photo, the dominant color makes the best primary, and the second-most dominant makes the best complementary accent.
For product photography, extract the dominant colors and use them to choose background colors for complementary contrast — a blue product pops best on a warm orange or neutral gray background.
Frequently Asked Questions
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