From cc4c9eeabd24ec564bdf7404b714e288d8379e8f Mon Sep 17 00:00:00 2001 From: Sergey Karchevsky Date: Sun, 17 Sep 2017 01:44:12 +0700 Subject: [PATCH] Fixed typo. --- 12/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/12/README.md b/12/README.md index 0832294..78a3cd0 100644 --- a/12/README.md +++ b/12/README.md @@ -177,7 +177,7 @@ Later in 2012 [Inigo Quilez wrote an article on how to make precise Voronoi bord -Inigo's experiments with Voronoi didn't stop there. In 2014 he wrote this nice article about what he calls [voro-noise](http://www.iquilezles.org/www/articles/voronoise/voronoise.htm), an function that allows a gradual blend between regular noise and voronoi. In his words: +Inigo's experiments with Voronoi didn't stop there. In 2014 he wrote this nice article about what he calls [voro-noise](http://www.iquilezles.org/www/articles/voronoise/voronoise.htm), a function that allows a gradual blend between regular noise and voronoi. In his words: *"Despite this similarity, the fact is that the way the grid is used in both patterns is different. Noise interpolates/averages random values (as in value noise) or gradients (as in gradient noise), while Voronoi computes the distance to the closest feature point. Now, smooth-bilinear interpolation and minimum evaluation are two very different operations, or... are they? Can they perhaps be combined in a more general metric? If that was so, then both Noise and Voronoi patterns could be seen as particular cases of a more general grid-based pattern generator?"*