A character recognition system using neural sub-networks for similarly shaped characters
Original Publication Date: 2002-Oct-10
Included in the Prior Art Database: 2003-Jun-20
Abstract: This disclosure describes a character recognition system that adapted two kinds of neural networks. After the primary network outputs the results, the system judges whether similarly shaped character sets exist in candidate characters. If they are detected, the system starts the secondary neural network processing for performing detail discrimination, and obtains the whole recognition result. Detail of invention: There are about eighty categories for Japanese Katakana set. Thus, it is very difficult to get high recognition ratio by single neural network processing. The reason is that many similarly shaped characters like (KO)", (YU)", and (YE)" exist in Katakana character set. Nevertheless, the probability that correct answer is included in top three candidates is enough high.