Design of multiple features and multilayer classifiers for handwritten character recognition
手写混合字符集识别的多特征多级分类器设计

A novel method for the recognition of commonly used handwritten Chinese characters in bank and digits was presented. Considering diverse classification requirements, different features were selected, an integration of clustering and Multi-layer Pereeptron neural networks was utilized. The experiment demonstrates that the proposed approach is promising.