A parallel processing algorithm for shrinking binary patterns to obtain single isolated elements, one for each pattern, is presented. This procedure may be used for counting patterns on a matrix, and a hardware implementation of the algorithm using large scale integrated tecnology is envisioned. The principal features of this method are the very small window employed (two-by-two elements), the parallel nature of the process, and the possibility of shrinking any pattern, regardless of the complexity of its configuration. Problems regarding merging and disconnection of patterns during the process as well as the determination of the maximum number of steps necessary to obtain a single isolated element from a pattern, are reviewed and discussed. An analogy with a neural network description, in terms of McCulloch-pitts “neurons” is presented.
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