Solving 2D-Pattern Matching with Networks of Picture Processors

Abstract

We propose a solution based on networks of picture processors to the problem of picture pattern matching. The network solving the problem can be informally described as follows: it consists of two subnetworks, one of them extracts simultaneously all subpictures of the same size from the input picture and sends them to the second subnetwork. The second subnetwork checks whether any of the received pictures is identical to the pattern. We present an efncient solution based on networks with evolutionary processors only, for patterns with at most three rows or columns. Afterwards, we present a solution based on networks containing both evolutionary and hiding processors running in 0{n-\-m-\-kl-\-k) computational (processing and communication) steps, where the input picture and the pattern are of size (n,m) and [k,l), respectively.

Networks of Picture Processors with Filtering Based on Evaluation Sets as Solvers for Cryptographic Puzzles Based on Random Multivariate Quadratic Equations

“…There, a picture is a two-dimensional array of elements belonging a finite set of symbols (alphabet). Traditionally, the NPP model is applied to problems concerning image processing, picture recognizability or pattern matching [8][9][10].…”