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copied!<p>How about defining an arbitrary resolution for your space, and calculate for each point in that matrix, a measure of the distance from that point to all dots, then you could make a "heat graph" and use a threshold to define the clusters.</p> <p>It's a nice exercise for processing, maybe later I will post a solution.</p> <p>EDIT:</p> <p>Here it is:</p> <pre><code>//load the image PImage sample; sample = loadImage("test.png"); size(sample.width, sample.height); image(sample, 0, 0); int[][] heat = new int[width][height]; //parameters int resolution = 5; //distance between points in the gridq int distance = 8; //distance at wich two points are considered near float threshold = 0.5; int level = 240; //leven to detect the dots int sensitivity = 1; //how much does each dot matters //calculate the "heat" on each point of the grid color black = color(0,0,0); loadPixels(); for(int a=0; a<width; a+=resolution){ for(int b=0; b<height; b+=resolution){ for(int x=0; x<width; x++){ for(int y=0; y<height; y++){ color c = sample.pixels[y*sample.width+x]; /** * the heat should be a function of the brightness and the distance, * but this works (tm) */ if(brightness(c)<level && dist(x,y,a,b)<distance){ heat[a][b] += sensitivity; } } } } } //render the output for(int a=0; a<width; ++a){ for(int b=0; b<height; ++b){ pixels[b*sample.width+a] = color(heat[a][b],0,0); } } updatePixels(); filter(THRESHOLD,threshold); </code></pre> <p>EDIT 2 (slighly less inefficient code but same output): </p> <pre><code>//load the image PImage sample; sample = loadImage("test.png"); size(sample.width, sample.height); image(sample, 0, 0); int[][] heat = new int[width][height]; int dotQ = 0; int[][] dots = new int[width*height][2]; int X = 0; int Y = 1; //parameters int resolution = 1; //distance between points in the grid int distance = 20; //distance at wich two points are considered near float threshold = 0.6; int level = 240; //minimum brightness to detect the dots int sensitivity = 1; //how much does each dot matters //detect all dots in the sample loadPixels(); for(int x=0; x<width; x++){ for(int y=0; y<height; y++){ color c = pixels[y*sample.width+x]; if(brightness(c)<level) { dots[dotQ][X] += x; dots[dotQ++][Y] += y; } } } //calculate heat for(int x=0; x<width; x+=resolution){ for(int y=0; y<height; y+=resolution){ for(int d=0; d<dotQ; d++){ if(dist(x,y,dots[d][X],dots[d][Y]) < distance) heat[x][y]+=sensitivity; } } } //render the output for(int a=0; a<width; ++a){ for(int b=0; b<height; ++b){ pixels[b*sample.width+a] = color(heat[a][b],0,0); } } updatePixels(); filter(THRESHOLD,threshold); /** This smooths the ouput with low resolutions * for(int i=0; i<10; ++i) filter(DILATE); * for(int i=0; i<3; ++i) filter(BLUR); * filter(THRESHOLD); */ </code></pre> <p>And the output with (a reduced) Kent sample:</p>

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