Pyramid computation of neighbor distance statistics in dot patterns

This paper describes an algorithm for computing statistics of Voronoi neighbor distances in a dot pattern, using a cellular pyramid computer, in a logarithmic number of computational steps. Given a set of dots in a square region of the digital plane, the algorithm determines with high probability the Voronoi neighbors of the dots in the interior of the region and then computes statistics of the neighbor distances. An algorithm of this type may account for the ability of humans to perceive at a glance whether the dots in a pattern are randomly or regularly spaced, i.e., their neighbor distances have high or low variance.