Analysis of global pattern features

A fundamental method for analysing the global features of visual patterns is presented. Pattern features are considered to be synonomous with non-random distributions in the pattern statistics. In particular, the statistics of the chords of the patterns are considered, leading to the histograms of the chord lengths and angles. Peaks in these histograms indicate the presence of structure in the pattern. It is demonstrated how the points of the pattern contributing to this structure can be enhanced and/or extracted.

It is argued that this is a more fundamental way of obtaining pattern features than other ad hoc methods.

The chord space approach allows analytic solutions to be easily obtained for idealized patterns such as circles, parallel lines, etc.

A method for implementing the algorithms on a parallel processor is indicated.