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Extract dominant colors from images using various algorithms including k-means clustering and histogram analysis
Execution
Fill in the form, run the tool, and review the result in one place.
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Tool usage guide
The Image Color Extractor allows you to precisely identify and pull dominant color palettes from any image using advanced algorithms like K-Means clustering, histogram analysis, and median cut.
Background
A designer needs to extract a professional color palette from a client's high-resolution logo to use in a brand identity kit.
Problem
Manually picking colors from a logo is imprecise and inconsistent.
How to use
Upload the logo, select 'Median Cut' for high quality, and set the color count to 5.
algorithm: median-cut, colorCount: 5, colorFormat: hexOutcome
A precise 5-color HEX palette that perfectly matches the brand's visual identity.
Background
A developer is building a feature where the application interface adapts its accent colors based on the user's uploaded avatar.
Problem
Need to extract dominant colors while avoiding neutral backgrounds like white or black.
How to use
Upload the avatar, enable 'Ignore White' and 'Ignore Black', and use the K-Means algorithm for fast processing.
Use K-Means for speed, Histogram for simple frequency analysis, or Median Cut for high-quality, accurate color representation.
Yes, you can enable the 'Ignore White Colors' or 'Ignore Black Colors' checkboxes to filter out neutral tones from your palette.
The tool supports JPEG, PNG, WebP, GIF, BMP, and TIFF formats.
You can extract between 1 and 20 dominant colors per image.
It determines how many pixels are analyzed from the image; higher values increase accuracy but may take slightly longer to process.
algorithm: kmeans, ignoreWhite: true, ignoreBlack: true, colorCount: 3Outcome
A clean set of 3 vibrant accent colors extracted from the avatar, ready to be applied to CSS variables.