RECOGNIZING PATTERNS IN PHOTOGRAPHS.
Scientific rept. no. 1,
UTAH STATE UNIV LOGAN ELECTRO-DYNAMICS LABS
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The problem of recognizing patterns in photographs is considered. It is assumed that the patterns to be classified are exactly known, and that the photograph is sampled and quantized to form a binary vector. The optimum classification procedure for the general case involves nonlinear data processing on this vector. In two important special cases, however, this optimum procedure reduces to one which uses correlation or matched-filter techniques. The analysis applies not only to the specific problem described here, but to any situation in which the patterns to be classified may be represented by binary vectors provided the appropriate assumptions are satisfied. An important example is the so-called property-list description of a pattern. Author