A Metasynthetic Approach for Handwritten Chinese Character Recognition
一种识别手写汉字的多分类器集成方法

As a high-level integration approach, metasynthesis has drawn much attention. In this paper, a metasynthetic approach for combination of multiple classifiers is proposed. As a first step, a linear integration model is built. In this model, not only the degree of the similarity between the input and its ranked candidates are appled, but also the supporting effects of multiple candidates are taken into account, and their contributions to the integration result is expressed by a linear function. Then, an algorithm for automatically calculating the arguments of the model through supervised learning is provided. Experiments on metasynthesis of three individual classifiers for handwritten Chinese character recognition are given to demonstrate the effectiveness of our method.