Segmentation of handwritten Japanese character strings with Hopfield type neural networks

Whereas a character segmentation is an essential pre-process for performing a character recognition, this has been an extremely complicated task for Japanese document recognition. The difficulties of it are due to the irregularities of sizes and disposition of Japanese characters in addition to an existence of separated characters. Thus, we have developed a new segmentation method with a Hopfield type neural networks and applied it to handwritten Japanese character strings. A general constraining conditions for segmentation of Japanese characters is expressed as energy functions in the networks and the networks can perform segmentation of Japanese character strings pliably. Our experimental result showed a probability of correct segmentation of 82.8% in contrast to 75.9% obtained by the conventional method.