Handprinted Kanji character recognition was the most important research topic for 1980s. Today there are several commercial products of handprinted Kanji OCR, but there are many unsolved problems. In this paper three types of research approach are focused for handprinted Kanji character recognition. The first approach is directional pattern matching, which is generally applied to handprinted Kanji character recognition. The second approach is potential field feature extraction, which activated Kanji character recognition research in the early stage of research. The third approach is shape matching. This paper surveys these research approaches, and both contributions and problems of them are discussed.

This paper shows that when a pattern matching method used in optical character readers is highly accurate, it can be used effectively in on-line Japanese character recognition. Stroke matching methods used in previous conventional on-line character recognition have restricted the number and the order of strokes. On the other hand, orientation-feature pattern matching methods avoid these restrictions. The authors have improved a pattern matching method with the development in the flexible pattern matching (FPM) method, based on nonlinear shape normalization and nonlinear pattern matching, which includes the normalization-cooperative feature extraction (NCFE) method. These improvements have increased the recognition rate from 81.9% to 95.9%, when applied to the off-line database ETL-9 from the Electrotechnical Laboratory, Japan. When applied on-line to the examination of 151,533 Kanji and Hiragana characters in 3,036 categories, the recognition rate achieved 94.0%, while the cumulative recognition rate within the best ten candidates was 99.1%.