Rotary Chinese character identifying method based on convolution neural network model

• Main Authors: DING YANFANG, WANG ZHIXIN, GAO XUE, SONG XUCHEN, YANG WEN
• Format: Patent
• Language: Chinese; English
• Published: 15.02.2017
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS

The invention provides a hand-written Chinese character rotation-independent identifying method based on a convolution neural network. The method includes the steps of building a Caffe deep learning framework platform containing a plurality of convolution neural network models on a graphics processor, preparing a training data set and a test data set with labels, training the convolution neural network models to identify primary-level hand-written Chinese characters on the graphics processor by using the data sets, and inputting original images of hand-written Chinese characters in HCL2000 database and images rotated randomly in various directions into the convolution neural network models to train the network, and finally inputting unknown rotated Chinese characters for testing to obtain the identification result of the Chinese character images. The method has the advantages of high smart level, simple method, accurate classification and rapid detection speed. The method has good identification performance f