A breathing Perlin Noise

This algorithm is based on the sacalled Perlin Noise. It is a noise function based on pseudorandom gradient values at grid points. The distribution of the variations is minimal and makes the visual output appear "more organic", as transitions move smoother than with a simple random factor.

The Perlin Noise function was developed by Ken Perlin in 1983 as a result of his frustration with the "machine-like" look of computer-genarated imagery (CGI) at the time.

My approach was to map the Perlin Noise distribution to the change of an ellipse diameter, simulating a shape breathing slightly irratic. For the practical applicagtion scenario I imagined a physical form in real life in form of a meditation guide or breathing instructor at a lung healing facility. In this case one would rather use the sinus/cosinus function to make the breathing even more regularly.

You can check out the code on the following GitHub repository.