💡 Click any pixel on the preview to sample exact color coordinates
File Info
image.png
Dimensions
0 × 0 px
File Size
0 KB
Average Color
#000000
Dominant Hue
#000000
📊 RGB Channel Intensity Histogram (256 Bins)
■ Red■ Green■ Blue
Export Palette:
📖 Complete Guide
Analyze Image Colors Online
A fast, client-side color extraction engine that uses K-Means++ clustering and HTML5 Canvas pixel sampling to generate dominant palettes, color histograms, and mathematical color metrics.
Color plays a fundamental role in visual design, brand identity, and photography. Understanding the precise chromatic composition of an image allows designers and developers to build cohesive color schemes, verify WCAG accessibility contrast, and extract CSS variables in seconds.
Rather than relying on arbitrary pixel sampling, ReducerImage executes K-Means++ Euclidean distance clustering across the full 3D RGB color gamut. Every dominant swatch represents the true centroid of a mathematically grouped color cluster with an exact pixel percentage frequency.
📊 Color Space Metrics
Color Model & Mathematical Specification
Overview of supported color representations, conversion formulas, and accessibility criteria.
According to Web Content Accessibility Guidelines (WCAG 2.1), standard text requires a minimum contrast ratio of 4.5:1 (Level AA) or 7.0:1 (Level AAA) against its background. Our analyzer automatically calculates relative luminance ($Y = 0.2126R + 0.7152G + 0.0722B$) for every extracted palette color to verify legibility against pure white and black surfaces.
⚡ Extraction Pipeline
How K-Means Color Clustering Functions
Our client-side color analysis pipeline executes in four synchronized steps:
Phase 1
🖼️
Pixel Reading
Extracts 32-bit RGBA pixel buffers, discarding fully transparent pixels to prevent artificial color bias.
Phase 2
🎯
K-Means++ Seeding
Seeds initial centroids with maximum Euclidean distance spread across the 3D RGB color gamut.
Phase 3
🔄
Iterative Centroids
Iterates pixel assignments until centroid convergence, calculating accurate cluster percentages.
Phase 4
📦
Multi-Format Export
Generates color histograms, accessibility metrics, CSS variables, and downloadable JSON/CSV files.
📋 Step-by-Step Guide
How to Extract Colors from Images in 8 Easy Steps
Follow this simple workflow to generate color palettes and inspect individual pixels.
1
Upload Image
Drag & drop or select your JPG, PNG, WebP, BMP, or GIF.
2
Automatic Analysis
The engine automatically clusters pixels into dominant hues.
3
Adjust Color Count
Choose between 3 to 12 palette colors dynamically.
4
Sort Palette
Sort by Dominance (%), Hue angle, or Lightness.
5
Eyedropper Inspect
Click any pixel on the preview to sample exact coordinates.
6
Inspect Histogram
View the 256-bin RGB channel intensity distribution chart.
7
1-Click Copy
Click any swatch card to copy its exact HEX code.
8
Export Palette
Download as JSON, CSV spreadsheet, or copy CSS Variables.
🧰 Free Utility Suite
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Answers to common questions about K-means color clustering, HEX/RGB conversions, and palette exports.
Image color analysis is the automated extraction and statistical evaluation of color data across an image's pixel matrix, identifying dominant palettes, average colors, brightness, and color frequencies.
Dominant colors are extracted using K-Means++ clustering in 3D RGB color space, grouping millions of image pixels into cohesive centroid color clusters sorted by frequency percentage.
A dominant color is a hue cluster that represents a significant percentage share of visible pixels in an image.
HEX (hexadecimal) is a 6-character code (e.g. #EF4444) representing red, green, and blue light channels from 00 to FF, widely used in web development and graphic design.
RGB represents colors as three 8-bit integer channels (Red, Green, Blue) ranging from 0 to 255 (e.g. rgb(239, 68, 68)).
HSL represents colors via Hue (0° to 360°), Saturation (0% to 100%), and Lightness (0% to 100%), providing an intuitive human-centric color model.
HSV (Hue, Saturation, Value) or HSB (Hue, Saturation, Brightness) defines color based on the intensity of light, commonly used in digital painting software.
No. Fully transparent pixels (alpha = 0) are excluded from clustering to prevent artificial black or white skewing in PNG and WebP graphics.
Yes. The interactive canvas eyedropper allows you to click or hover over any point on the image to inspect its exact pixel coordinates, HEX, RGB, and HSL values.
Yes. You can export the analyzed color palette as structured JSON, CSS Variables, CSV spreadsheets, or copy individual HEX codes in one click.
No. The analyzer reads pixel buffers in memory for statistical calculations only; your original source file remains completely unmodified.
No. All pixel reading, K-means clustering, and histogram rendering execute 100% locally in your web browser via HTML5 Canvas.