NOTE ON 2-DIMENSIONAL PATTERN-MATCHING BY OPTIMAL PARALLEL ALGORITHMS

We discuss techniques for constructing parallel image identification algorithms : cutting images into small factors, and compressing images by a parallel reduction of large number of such independent factors into smaller objects. A version of Kedem Landau Palem algorithm for parallel one-dimensional and two-dimensional rectangular image recognition on a CRCW PRAM is presented. The crucial part in KLP algorithm is a suffix-prefix matching subprocedure. In our algorithm such a subprocedure is omitted. A novel algorithm for pattern-matching is proposed, more directly designed for two-dimensional objects. It does not use the multi-text/multi-pattern approach as in KLP algorithm. The importance of five types of factors in strings and images is emphasized. A new useful type of two-dimensional factors is introduced : thin factors.