University of Bologna

Dipartimento di Elettronica, Informatica e Sistemistica

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Computer Recognition of Hand-Written Characters using the Distance Transform

Zs. M. Kovacs and R. Guerrieri


A new statistical classifier for hand-written character recognition is presented. The system features a preprocessing phase for image normalization and a distance transform applied to the normalized image, which converts a B/W picture into a gray scale one. A k-Nearest-Neighbor classifier follows, based on the distance transform and a suitable metric. The system has an accuracy of 98.96% when applied to the U.S. Post Office ZIP code database, at 0.98% error rate

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