Shin Katoh

DRS: a workstation-based document recognition system for text entry

Document recognition system (DRS), a workstation-based prototype document analysis system that uses optical character recognition (OCR), is described. The system provides functions for image capture, block segmentation, page structure analysis, and character recognition with contextual postprocessing, as well as a user interface for error correction. All the functions except image capture and character recognition have been implemented by means of software for the Japanese edition of OS/2.<<ETX>>

A document recognition system and its applications

This paper describes a document entry system called the Document Recognition System (DRS), which facilitates the conversion of printed documents into electronic form. DRS was developed on a personal computer (PC) with an adapter card for recognizing more than 3000 Kanji characters. It provides a flexible framework for object-oriented management of data and processing modules. The framework allows the user to change the combination of processing modules and to select pipelining (parallel processing) or sequential processing. DRS includes processing modules for layout analysis functions such as blob detection, block segmentation, and model matching, and for character recognition functions such as Kanji character recognition, Japanese postprocessing, postprocessing by a user, and error correction through a user interface. The character recognition functions on the card and the other processing-related recognition functions on the PC work cooperatively in the proposed framework. Within the basic framework, we have customized DRS for practical applications. Examples of successful applications-entry into a text database, creation of an electronic catalog, entry of family registration data, and entry of tag data in a manufacturing process-provide evidence of the processing accuracy and robustness of the framework.

An on-line character recognition system for effective Japanese input

An online character recognition system has been developed in order to allow effective Japanese entry via a pen interface. The system consists of handwriting recognition, contextual postprocessing, and enhanced Kana-to-Kanji conversion subsystems. The recognition subsystem uses a hybrid algorithm consisting of a pattern matching discriminator and a neural network verifier. Special care was taken to improve recognition of non-Kanji and simple Kanji characters frequently used in fast data entry. The postprocessor predicts consecutive characters on the basis of biagrams modified by the addition of parts of speech and substitution of macro characters for Kanji characters. A Kana-to-Kanji conversion method designed for ease of use with a pen interface is also integrated into the system. In an experiment in which 2499 samples of Kanji and non-Kanji characters were taken from 20 subjects, it was observed that the original recognition accuracy of 85% (the result obtained by using the pattern matching discriminator) was improved to 91.5% by adding the hybrid algorithm, and that it was further improved to 94.5% by adding the postprocessor. Improved recognition accuracy.<<ETX>>