ImageCalcGen

Advanced Image Calculation & Generation Tools

Color Palette Generator

Extract and generate beautiful color palettes from your images with advanced color analysis.

Upload Image

Results

Upload an image to see preview

#4F46E5

RGB(79, 70, 229)

#10B981

RGB(16, 185, 129)

#F59E0B

RGB(245, 158, 11)

#EF4444

RGB(239, 68, 68)

#3B82F6

RGB(59, 130, 246)

#8B5CF6

RGB(139, 92, 246)

Color Distribution

About Color Palette Generator

The Color Palette Generator extracts dominant colors from your images using advanced clustering algorithms. It's perfect for designers, artists, and developers who want to create harmonious color schemes based on real images.

How It Works

When you upload an image, the tool:

  1. Analyzes the image pixel by pixel to understand its color composition
  2. Groups similar colors together using the selected algorithm (K-means clustering by default)
  3. Identifies the most dominant colors based on their frequency and visual impact
  4. Returns a palette of colors with their HEX, RGB, and HSL values
  5. Visualizes the color distribution in the image

Key Features

  • Multiple Algorithms: Choose between different color extraction methods for varied results
  • Color Spaces: Analyze colors in RGB, HSL, or CIELAB spaces for different needs
  • Custom Palette Size: Extract from 5 to 10 dominant colors from your image
  • Visualization: See how colors are distributed in your image with interactive charts
  • Color Codes: Get HEX, RGB, and HSL values for easy use in design tools

Use Cases

  • Branding: Extract colors from logos or product images to create brand palettes
  • Web Design: Generate color schemes that match hero images or product photos
  • Art: Analyze paintings or photographs to understand color composition
  • Marketing: Create visually consistent materials based on key images

Technical Details

The tool processes images entirely in your browser using JavaScript. No image data is uploaded to any server, ensuring complete privacy. The algorithms work by:

K-means Clustering: Groups colors into clusters based on similarity, then finds the central color of each cluster.

Median Cut: Divides the color space into smaller boxes containing similar colors, then averages each box.

Color Thief: Uses a combination of quantization and histogram analysis to find dominant colors.

Different color spaces can produce different results because they measure color similarity in different ways. RGB is standard for screens, HSL is more intuitive for human perception, and CIELAB is designed to match human vision.