A Computational Model for Periodic Pattern Perception Based on Crystollagraphic Groups

Carnegie Mellon University, Pittsburgh PA

Investigators

Abstract

The proposed work addresses a computational model for periodic pattern perception based on the mathematical theory of crystallographic groups. The model to be built will have a capability of isolating underlying periodic patterns in images. Results of the work are likely to enrich methods of image processing of symmetric structures. Other applications include pattern indexing (textile, psychology), image reproduction/compression, gait analysis, among others.