Image Color Extractor
Upload any image to extract its dominant color palette. Get HEX and RGB codes for each color. Choose 5–16 colors. All processing in your browser.
Drop an image here or click to browse
JPG, PNG, WebP, GIF supported
How to use Image Color Extractor
Extract the dominant color palette from any image — upload a photo, product shot, or design screenshot and instantly get the top 5–10 colors as HEX swatches. Perfect for building a brand palette from a logo, matching a website's color scheme to a hero image, or analyzing the color composition of competitor designs.
- Upload an image (JPG, PNG, or WebP) using the file picker or drag-and-drop.
- The tool analyzes the pixel data using k-means clustering to find dominant colors.
- Review the extracted palette sorted by dominance (largest color area first).
- Click any swatch to copy its HEX value.
- Export the full palette as JSON, CSS variables, or a swatch PNG.
Your data never leaves your device — 100% private processing.
How dominant color extraction works
The tool samples pixels from the uploaded image (downscaled to ~200×200 for performance), converts them to LAB color space for perceptual accuracy, then applies k-means clustering to find the most representative group centroids. Each centroid represents a dominant color. The number of clusters (5–10) controls palette size. LAB clustering produces more perceptually meaningful groupings than RGB clustering — similar-looking colors end up in the same cluster even if their RGB values differ significantly.
Practical applications
Brand design: upload a company logo to extract its exact hex values for the design system. Product photography: extract dominant colors to auto-tag product listings (e.g., "navy blue sofa") or generate matching background colors. Interior design: upload a room photo to build a complementary paint color palette. Data visualization: extract a natural color palette from a themed photograph for use in chart color scales. Social media: match headline text colors to the dominant colors in a background photo for visually cohesive posts.
Glossary
- K-means clustering
- A machine learning algorithm that groups data points into K clusters by minimizing the distance to the nearest centroid.
- Dominant color
- The color occupying the largest area in an image after clustering nearby shades together.
- Color quantization
- Reducing the number of distinct colors in an image while preserving its visual appearance — the basis of palette extraction.
- Centroid
- The central representative point of a cluster — in color extraction, the average color of all pixels assigned to that cluster.
Related reading
Frequently Asked Questions
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Why use Image Color Extractor?
- Converts between HEX, RGB, HSL, HSV, and CMYK instantly
- Accessibility contrast checker built in
- Generates harmonious palette variations from a single colour
- Export-ready CSS variables and design tokens
Common use cases
- Pick brand colours that meet WCAG accessibility standards
- Generate a complementary palette from a logo colour
- Convert Figma HEX codes to CSS rgb() for developers
- Create a gradient from two brand colours
- Verify sufficient contrast for text on coloured backgrounds
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