Image Color Palette Extractor
Upload any image and instantly extract a beautiful color palette. Our Image Color Palette Extractor uses K-Means clustering to identify dominant, vibrant, muted, and accent colors - automatically classifying each into one of six color profiles (Vibrant, Muted, Dark Vibrant, Dark Muted, Light Vibrant, Light Muted). Each extracted color includes its HEX, RGB, and HSL values, the closest CSS named color, a dominance percentage showing how much of the image it represents, and a design usage suggestion. Export individual colors or download the full palette as JSON. All processing is 100% local - your images never leave your browser. Free, no signup required.
Drop an image here, or click to browse
Supports JPG, PNG, WebP, GIF - processed entirely in your browser
Upload Any Image
Supports JPG, PNG, WebP, and GIF formats. Images are processed entirely in your browser - nothing is uploaded to any server. Drag and drop or click to select.
Intelligent Color Extraction
Uses K-Means clustering to identify the most representative colors in your image. The algorithm analyzes thousands of pixels to find dominant, vibrant, muted, and accent colors with high accuracy.
Classified Color Profiles
Each extracted color is classified into a profile - Vibrant, Muted, Dark Vibrant, Dark Muted, Light Vibrant, or Light Muted - similar to the Android Palette library. Shows the closest CSS named color with HEX, RGB, and HSL values.
Export & Copy
Copy individual colors with one click or download the full palette as a JSON file. Each color includes its profile, dominance percentage, named color match, and usage suggestion.
Design Inspiration
Extract color palettes from photographs, artwork, and brand assets you admire. Use the extracted colors as a starting point for your own designs - ensure your palette captures the mood of your inspiration.
Frontend Development
Generate design tokens directly from brand images, logos, or hero images. The extracted colors come with CSS variable-ready HEX values and WCAG-aware usage suggestions.
Brand Identity Design
Analyze competitor brand imagery or create a cohesive palette from brand photography. The profile classification (vibrant, muted, etc.) helps balance your color system with the right mix of bold and subtle colors.
Digital Art & Photography
Understand the color composition of your photographs and artwork. See which profiles dominate your image and discover the named color closest to each extracted color.
Theme Design
Extract a theme palette from a wallpaper or background image. Use the colors to build a cohesive dark/light mode - dark muted colors for surfaces, vibrant for accents, light muted for backgrounds.
Product & Fashion Design
Extract colors from product photos or fashion lookbooks to build coordinated colorways. The dominance metric shows which colors are most prominent in the original image.
How the Color Extraction Works
The tool uses K-Means clustering - an unsupervised machine learning algorithm - to group similar-colored pixels together into clusters. Each cluster centroid becomes a color in your palette. The algorithm runs for up to 12 iterations to converge on the most representative colors, ensuring consistent results across different images.
Image Processing Pipeline
When you upload an image, it is drawn onto an offscreen canvas at a maximum dimension of 400px for performance. Pixels are sampled at a configurable rate (every 4th pixel) to get a representative dataset. Near-white, near-black, and transparent pixels are filtered out to focus on meaningful colors.
Color Profile Classification
Each extracted color is classified into one of six profiles based on its HSL saturation and lightness: Vibrant (high sat, medium light), Muted (low sat, medium light), Dark Vibrant (high sat, dark), Dark Muted (low sat, dark), Light Vibrant (high sat, light), and Light Muted (low sat, light). This follows the same approach as the Android Palette support library.
100% Privacy-First Processing
All image processing happens entirely in your browser using the Canvas API and Web Workers. Your images are never uploaded to a server, stored, or transmitted. Once you close the page, all extracted data is gone - nothing is saved or logged.
CSS Named Colors Reference
Search, filter, and copy all 148 CSS named colors with HEX, RGB, and HSL values - filter by 12 color families.
Color Palette Generator
Generate 5-color palettes from any base color using harmony rules. Lock individual colors and regenerate. Export as CSS, SCSS, or Tailwind.
Noise Texture Generator
Generate white noise and Perlin noise textures at custom sizes with adjustable intensity, color, and scale.
Brand Color Lookup
Search and copy brand colours for 200+ major brands - Apple, Google, Meta, Nike, and more. HEX and RGB values.
The tool uses K-Means clustering to analyze the pixels in your image and group them by color similarity. Each group's average color becomes part of the extracted palette. The algorithm identifies the most representative colors - not just the most common - and classifies each one into a profile like Vibrant, Muted, or Dark using HSL saturation and lightness thresholds.
The tool supports all standard web image formats: JPEG, PNG, WebP, GIF, BMP, and SVG. Images are processed using the browser's built-in image decoding and Canvas API, so support matches what your browser supports natively.
Each extracted color is classified based on its saturation and lightness: Vibrant colors are highly saturated with medium lightness - ideal for accents. Muted colors have low saturation - great for backgrounds. Dark/Light variants indicate the lightness level. This classification follows the same approach as the Android Palette support library, helping you build balanced color systems.
No. All image processing is done entirely in your browser using JavaScript and the HTML Canvas API. Your images never leave your device. The tool works fully offline once the page is loaded.
The tool extracts up to 8 colors by default, ensuring a diverse selection across different color profiles. The algorithm first identifies 16 candidate clusters, then selects the most representative colors while ensuring variety across the six color profiles (Vibrant, Muted, Dark Vibrant, etc.).
K-Means clustering with 12 iterations provides consistently accurate results for most images. The algorithm samples pixels at every 4th pixel position to get a representative dataset while staying performant. Near-white and near-black pixels are filtered out to avoid washing out the palette with background or shadow colors.
Yes. Each color comes with production-ready HEX, RGB, and HSL values plus a usage suggestion based on its profile. Vibrant colors are recommended for actions and accents, muted colors for surfaces and backgrounds. You can also download the full palette as a JSON file for use in design tokens or style dictionaries.
For each extracted color, the tool finds the closest match from all 148 CSS named colors using a weighted Euclidean distance formula. This gives you a human-readable name for the color - useful for design communication and documentation.