A self-organizing hierarchical classifier for multi-lingual large-set oriental character recognition

摘要

In this paper, we propose a practical scheme for multi-lingual, multi-font and multi- size large-set Oriental character recognition using a self-organizing hierarchical neural network classifier. In order to absorb the variation of the character shapes in multi-font and multi-size characters, a modified nonlinear shape normalization method based on dot density was introduced, and also to represent the different topological structures of multi- lingual characters effectively, a hierarchical feature extraction method was adopted.