Overview
Introduction
This tool applies a real Voronoi diagram (a classic computational-geometry construction) to a PNG's pixels, entirely in your browser.
The result is a mosaic-like reinterpretation of the source image where each region takes its color from a single sampled point.
What Is PNG to Voronoi Diagram Converter?
A client-side PNG-to-Voronoi-diagram converter that scatters a set number of site points across the image using a seeded deterministic random generator, then assigns every pixel to its nearest site and colors it using the pixel sampled at that site's location.
An optional edge-drawing pass darkens boundary pixels between neighboring cells, making the underlying diagram structure visible rather than just producing a mosaic.
How PNG to Voronoi Diagram Converter Works
For a chosen cell count and seed, the tool generates that many pseudo-random (x, y) site positions within the image bounds using a small, fast, fully deterministic PRNG (mulberry32), so the same inputs always produce the same layout.
Every output pixel then finds its nearest site by brute-force distance comparison, is colored with the source image's pixel color at that site's coordinates, and (if edge drawing is enabled) is overridden to black when its right or bottom neighbor belongs to a different site's cell.
When To Use PNG to Voronoi Diagram Converter
Use it to create a stylized, low-poly-esque mosaic version of a photo or graphic for a background, thumbnail, or decorative asset.
It's also a fun way to visualize how Voronoi diagrams partition space, using a real image as the backdrop instead of abstract points.
Often used alongside PNG Rotator and PNG Dimensions Finder.
Features
Advantages
- Runs entirely client-side; your image never leaves the browser.
- Fully deterministic for a given seed, so results are reproducible rather than random every time.
- Optional edge outlining turns a simple color mosaic into a genuine, readable diagram.
Limitations
- The nearest-site search is brute-force, so processing time grows with width times height times cell count - very large images combined with high cell counts can take a while.
- Cell count is capped at 300 to keep processing times reasonable in the browser.
Examples
Best Practices & Notes
Best Practices
- Start with a lower cell count (20-60) for a clearly faceted look; higher counts approach the original image's detail.
- Keep edge drawing on if you want the result to read as a diagram rather than a blurry mosaic.
Developer Notes
The pure algorithm lives in a lib function operating on a plain PixelBuffer with no DOM dependency, using a seeded mulberry32 PRNG for reproducible site placement and a brute-force O(width x height x cellCount) nearest-neighbor search per pixel, which is simple, correct, and fast enough for typical tool-sized images and cell counts.
PNG to Voronoi Diagram Converter Use Cases
- Creating a stylized low-poly-style image effect
- Generating a reproducible, seed-controlled mosaic background
- Demonstrating Voronoi diagrams visually using a real photo
Common Mistakes
- Setting a very high cell count on a large image and expecting an instant result - processing time scales with both.
- Expecting two different seeds to produce the same layout - only an identical seed and cell count reproduce identical results.
Tips
- Try a few different seeds at the same cell count to quickly compare several distinct mosaic layouts.
- Turn edges off if you want a smoother, more painterly mosaic look instead of a diagram with visible borders.