A Handwritten Chinese Character Recognition based on Convolutional Neural Network and Median Filtering

Abstract

With the rapid growth of researches toward computer vision and pattern recognition, methods that based on convolutional neural network (CNN) have shown unique advantages on handwritten characters recognition, also provided impressive results. This paper proposes a model based on CNN to deal with matters of handwritten Chinese character recognition. Different with conventional recognition system, in this model, input images are preprocessed by median filtering to smooth and reduce noise. For testing the stability and performance of the model, two testes are managed respectively. In integral test, experimental results show that the accuracy rate of recognition approach to 90.91% after 5000 times training, mean square error is decreased to 0.0079 at last. Meanwhile, this system also has a good performance at real-time test.