Handwritten Chinese character recognition (HCCR) is a typical large vocabulary pattern recognition problem. Handwritten Chinese characters are characterized with large vocabulary, complex structure, lots of similar characters and serious irregular variations of shapes. So HCCR is a very difficult problem and commonly regarded as one of the ultimate goals of character recognition research. In the research of large vocabulary recognition, matching approaches are frequently adopted because it is easy to be realized. But the classification performance of mateh'mg approaches is not good. In recent years artificial neural network (ANN) has been successfully applied into pattern recognition. It has been proved theoretically that ANN can simulate the Bayesian optimal decision. The distributed and parallel information processing way of ANN accords with reality. Moreover, the learning mechanism of ANN make it is very convenient to realize human-machine integration emphasized in Met synthesis. However, in case of large vocabulary recognition such as HCCR, successful work on classification and integration with AN'N is scarce. Almost all of the previous reports on this topic adopted strategy of problem decomposition, and the performance of system were not improved evidently. In this dissertation creative work is that the approach of classification and integration based on ANN is proposed. Different from previous report, the original problem is considered in a holistic and systematic way, each ANN has the capability to process the whole categories. So the problem of HCCR can be solved in the same way as numeral recognition. It is worth to be pointed out that our work starts from the strategy of human-machine integration, which is emphasized in met synthesis and realized through supervised learning. Human- machine integration can decrease the complexity of original problem. In a integrated system, different supervised learning ways are designed for different layers, and the role of man appears in different stages of method design and system realization. The presentation and implementation of the approach of classification and integration with ANN in HCCR not only improve the Chinese character recognition research, but also provide a feasible way applying ANN to large vocabulary classification problems.
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