Stippling #2

Another attempt at stippling with a more basic relaxation approach but using multiple dot sizes to add texture.

Position starting points with rejection sampling, using the grayscale image as the density function.
Use Lloyd's algorithm to get a relaxed Voronoi diagram from the starting points.
Size the dots based on the darkness of the pixel at their position, then shrink them as much as necessary to avoid collisions - this could be done all at once but it seems to produce some splotchy artifacts, so instead they're shrunk a little bit at a time.

The heavy computation is done in a web worker to avoid locking up the page, and takes about 15-20 seconds to complete.

See also: Voronoi relaxation, Stippling, Philippe Rivière's CCPD Snowden

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="utf-8" />
  <style>
    canvas {
      display: block;
      width: 800px;
      height: 500px;
      margin: 0 auto;
    }
  </style>
</head>
<body>
<canvas width="1600" height="1000"></canvas>
<script src="https://d3js.org/d3.v5.min.js"></script>
<script src="stackblur.min.js"></script>
<script>

const canvas = document.querySelector("canvas"),
  context = canvas.getContext("2d"),
  img = new Image(),
  width = 800,
  height = 1000,
  threshold = 0.9,
  worker = new Worker("worker.js");

context.fillStyle = "#444";

img.onload = function() {
  // Draw image
  context.drawImage(img, 0, 0, width, height);

// Blur image to smooth it out
  StackBlur.canvasRGBA(canvas, 0, 0, width, height, 5);
  const density = getDensityFunction(context);

context.drawImage(img, 0, 0, width, height);

// Get initial points
  const points = generatePoints(density, 10000);

worker.onmessage = event => draw(event.data);

// Compute in worker
  worker.postMessage({ density, points, width, height, threshold });
};

img.src = "obama.png";

// Draw the points
function draw(points) {
  context.clearRect(width, 0, width, height);

points.forEach(function(point) {
    context.beginPath();

if (point.r) {
      context.arc(width + point[0], point[1], point.r, 0, 2 * Math.PI);
      context.fill();
    }
  });
}

function generatePoints(density, numPoints) {
// Generate starting points with rejection sampling against pixel brightness
  return d3.range(numPoints).map(function() {
    let x, y, d;

while (true) {
      x = Math.random() * width;
      y = Math.random() * height;

d = density[width * Math.floor(y) + Math.floor(x)];

if (Math.random() > d) {
        return [x, y, d];
      }
    }
  });
}

// Convert imageData into an array of brightness values from 0-1
function getDensityFunction(context) {
  const data = context.getImageData(0, 0, width, height).data;

return d3.range(0, data.length, 4).map(i => data[i] / 255);
}
</script>

https://d3js.org/d3.v5.min.js