Abstract
In this paper we study the problem of Chinese character recognition in video. We propose a series of algorithms on Chinese character division, tracking. Based on them we design a multi-level sorter. Firstly we extract the features of some samples and employ K-means clustering algorithm to carry on I level classification. Secondly, we employ the algorithm of multi back propagation neural network (MBPNN) to classify every category once again and we call it II level classification. Finally, we carry on the experiment and the testing result proves that these algorithms are effectively and recognition rate is higher than conventional back propagation neural network.
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