Javascript module for color quantization, based on Leptonica.

Incremental KMeans for Color Quantization

Small image utility featuring an implementation of the median-cut color quantization algorithm and Floyd-Steinberg dithering in C.

This demonstrates how to find the dominant colors in an image. Included are Swift and command-line(cpp) samples. The command-line version outputs a PNG file of the palette and a PNG image quantized to the resulting palette. The Swift version uses an Objective-C Category to extend UIImage and Objective-C Bridging Header to expose the extension to…

GUI tool for creating PNG8

Color Quantization using K-Means(Machine learning)

Bunnylin's Chromaticity Compressor, a color quantisation tool.

Coded Examples of Different types of Clustering Techniques...

Color quantization using k-means

Image color quantization using K-Means Clustering & OpenCV

A color quantization tool for images based on k-means clustering

Coloring an image with 'K' Colors using K-Means Coloring

Color quantization is the process of reducing number of colors used in an image while trying to maintain the visual appearance of the original image. In general, it is a form of cluster analysis, if each RGB color value is considered as a coordinate triple in the 3D colorspace.

Visualizing dominant colors and color quantization with k-means clustering

Apply color quantization to images using k-means clustering.

Implementing Artificial Neural Network training process in Python

This project is an attempt at performing color quantization using K-Means clustering. We also add our own touch by trying a different initialization strategy for the cluster centroids and qualitatively compare our results.

Color quantization with octrees and dithering