Self-similarity coding of random texture with applications to design and detection of complicated patterns

A dynamic scheme is presented for identifying generation processes of complicated patterns. Patterns with random textures are filtered to yield a discrete feature pattern. This feature pattern is successively expanded for estimating self-similar partition. A set of reduced affine mappings is specified through joint statistic-geometry analysis of the partition. The coding method is applied to design and detection of complicated patterns.