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Upload an image to extract its dominant color palette// analyze image and extract dominant color palette
Extract dominant colors from any image instantly. Get hex, RGB, HSL values and a full color palette from photos, screenshots, or design assets.
Drop image here
or click to browse
PNG · JPG · WEBP · GIF · BMP · SVGReady to analyze
Upload an image to extract its dominant color paletteDrag and drop any image file onto the upload zone, or click to browse your files.
Choose how many colors to extract (2–16) and your preferred output format: HEX, RGB, or HSL.
Click Extract Colors. Copy individual swatches or export the full palette as CSS variables.
The Dominant Color Picker uses a median-cut quantization algorithm to cluster the pixels of your image and identify the most statistically prominent colors. Unlike simple sampling, it accounts for color frequency and perceptual weight, giving you a palette that truly represents your image.
All processing happens entirely in your browser using the Canvas API — no image data is ever sent to a server.
No. All color extraction happens entirely within your browser using the HTML5 Canvas API. Your image data never leaves your device, making this tool completely private and GDPR-friendly.
Any format your browser can natively render: JPEG, PNG, WebP, GIF (first frame), BMP, and SVG. For best results use PNG or JPEG files under 10MB.
The tool uses median-cut quantization combined with pixel sampling. It divides the color space recursively, finds the median of each dimension, then returns the most prominent cluster centroids as your palette colors.
Quality controls the pixel sampling rate. Precise samples every pixel for maximum accuracy but is slower on large images. Fast samples every 5th pixel for instant results. Balanced is the recommended default for most images.
All three represent the same colors in different notations. HEX (#34d399) is most common in CSS and design tools. RGB (52, 211, 153) splits into red, green, blue channels. HSL (158°, 59%, 52%) represents hue, saturation, and lightness — great for programmatic color manipulation.
Yes. Click the CSS Vars button to copy the entire palette as CSS custom properties (variables) ready to paste into your stylesheet. Each color is named --color-1 through --color-N.
If your image has large areas of similar but not identical colors (like a gradient sky), the algorithm may return multiple nearby colors. Reduce the palette size or try the Precise quality setting to get more distinct results.
You can extract between 2 and 16 dominant colors per analysis. For most design work, 5–8 colors gives the best balance between detail and usability. Brand palette work typically uses 4–6 colors.
A dominant color picker is a tool that analyzes the pixel data of an image and identifies the most statistically prominent colors in it. Rather than simply picking random pixels, a proper dominant color extractor uses clustering algorithms to group similar colors and determine which color families represent the largest portions of your image. The result is a color palette that reflects the true visual character of your source image.
This JLV DevTools implementation processes your images entirely in the browser using the HTML5 Canvas API, with zero server-side processing. Your images stay on your device at all times.
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The algorithm behind this tool uses a technique called median-cut quantization, one of the most widely-used approaches for image color palette generation. Here's how it works step by step:
First, the image is drawn onto a hidden HTML5 Canvas element. The raw pixel data is then read using getImageData(), which returns an array of RGBA values — one set per pixel. To balance accuracy and speed, a configurable sampling step skips every N pixels (controllable via the Quality setting).
The sampled pixels are then sorted by the color channel with the highest range (red, green, or blue). The list is split at its median point into two equal buckets. This process repeats recursively — each bucket is sorted and split again — until we have as many buckets as the desired palette size. The average color of each bucket becomes one entry in the final palette.
The result is a palette where each color represents a distinct region of the image's color space, weighted by how many pixels fall into that region. This gives significantly better results than simply picking random pixels or sampling at regular grid positions.
Dominant color extraction has a wide range of practical applications in web development, design, and data visualization:
This tool outputs colors in three formats. Understanding the differences helps you choose the right one for your workflow:
HEX (#34d399): The most widely used format in web development. A six-character hexadecimal string where the first two characters represent red, the middle two green, and the last two blue. Range per channel: 00–FF. Use HEX when working in CSS, design tools like Figma, or when copy-pasting into code.
RGB (rgb(52, 211, 153)): Represents the same information as HEX but as three decimal integers (0–255) for red, green, and blue. RGB is useful when you need to perform mathematical operations on color values or work with canvas and image processing APIs.
HSL (hsl(158, 59%, 52%)): Stands for Hue, Saturation, and Lightness. Hue is the base color angle on the color wheel (0–360°). Saturation is the intensity (0% = gray, 100% = vivid). Lightness controls brightness (0% = black, 100% = white). HSL is far more intuitive for creating color variations — to make a color lighter, you increase the L value. This makes it ideal for building design systems and generating tints/shades programmatically.
The quality of your extracted palette depends heavily on the source image and your settings. Here are some tips to get the most accurate and useful results:
One of the most useful features of this tool is the ability to export your extracted palette directly as CSS custom properties. After extracting your colors, click the CSS Vars button to copy code like this to your clipboard:
:root {
--color-1: #1a1a2e;
--color-2: #16213e;
--color-3: #0f3460;
--color-4: #e94560;
--color-5: #f5f5f5;
}This output is immediately usable in any CSS file or style block. You can then reference var(--color-1) throughout your stylesheet, making it trivial to apply a consistent color theme derived from your source image across an entire project.
This tool uses the HTML5 Canvas API, which is supported in all modern browsers — Chrome, Firefox, Safari, Edge, and their mobile counterparts. No plugins, no server requests, no cookies. The only requirement is that your browser must be able to display the image format you upload.
Because all processing is local, this tool is suitable for use with confidential or proprietary images — brand assets, unreleased product mockups, client work — without any risk of data exposure.