Recognition of Printed Chinese Characters

Abstract

The problem of recognizing a large alphabet (1000 different characters) is approached using a two stage process. In the first stage of design, the data is partitioned into groups of similar characters by means of heuristic and iterative algorithms. In the second stage, peephole templates are generated for each character in such a way as to guarantee discrimination against other characters in the same similarity class. Recognition is preceded by establishing an order of search through the groups with a relatively small number of ``group masks.'' The character is then identified by means of the ``individual masks.'' through a threshold criterion. The effects on the error and reject rates of varying the several parameters in the design and test procedure are described on the basis of computer simulation experiments on a 20 000 character data set. An error rate of 1 percent with 7 percent rejects, is obtained on new data.