2D Cellular Automata for Feature Detection

This is a biologically inspired machine-vision scheme, designed to broadly mimic the human primary visual cortex using five-neighbor 2D cellular automata. The sample region (where is odd) is evaluated times. On each evaluation, the side length decreases by two, so the final point in the activation graph is a binary representation of whether the model "believes" the line to be horizontal or vertical, or whether the number of horizontal features has passed some threshold.

This came out of a research project done at the 2008 NKS Summer School.