J4 ›› 2016, Vol. 33 ›› Issue (5): 530-536.

• Image and Information Proc. • Previous Articles     Next Articles

An optical image recognition system for handwritten Chinese character recognition rate in cloud platform

Hu Xiaofang, Zhao Yuanli   

  1. 1Department of Electronic Information and Physics,Changzhi University,Changzhi Shanxi 046011,China;2 School of Physics and Engineering,Zhengzhou University,Zhengzhou 450001,China
  • Received:2015-12-16 Revised:2016-07-22 Published:2016-09-28 Online:2016-09-28

Abstract: For the feature extraction methods’ restrictions problem of handwritten chinese character recognition in traditional two handwritten cinese character recognition system, the paper proposes a identification system method which uses convolution neural network to automatically learn chinese characters similar characteristics. The method uses data from large handwritten cloud platform to train the model, generating similar frequency statistics based on a subset of, and further improve the recognition rate. Experimental results show that the recognition rate with respect to the traditional gradient-based feature support vector machine (SV and nearest neighbor classifier method, this method has improved to some extent.

Key words: Handwritten cinese character; Automatic learning; Convolution neural network; Cloud platform; Recognition rate