Decision tree design using a probabilistic model (Corresp.)

A sequential optical character recognition algorithm, ideally suited for implementation by means of microprocessors with limited storage capabilities, is formulated in terms of a binary decision tree. Upper bounds On the recognition performance are derived in terms of the stability of the digitized picture elements. The design process is described in detail. The algorithm is tested on single-font typewritten characters and the experimental and theoretical results are compared.