Research On Off-line Handwritten Chinese Character Recognition System

Off-line handwritten Chinese character recognition is a challenge in the field of pattern recognition. It will take an important part in many fields of our life, such as letter selecting, check recognition, report form disposing and handwritten manuscript auto-input. However, for Chinese characters are so much different when written by different people, the research on off-line Chinese character recognition develops evidently slower than many other character recognition researches.The system is mainly used for handwritten manuscript auto-input, The main work on this is as follows:1,In the step of preprocessing, smoothing, binarizing and normalizing is completed. Especially, different binarizing methods are used according to different paper backgrounds. Such as the examination partition methodology is used on character pictures of blank background and double-threshold methodology is used on the pictures with frame lines.2,Lots of researches and tests are done on Chinese characters segmentation, and blurry rules judgment segmentation method is chosen for the application of this recognition system is Chinese character auto-input.3,Some statistical and structural feature extraction methods are introduced and two new ones are used for two kinds of characters, such as elastic meshing directional features are proposed for handwritten printed characters and thinned Chinese character stroke features are used for normative general characters. Besides, element tracing method and cross spot stroke segment combination method are proposed to improve inflexion extraction and stroke segment combination.4,In the stage of recognition, two kinds of pre-classification methods are also used to do with the two kinds of above-mentioned features. We use error equilibrium distance to judge elastic meshing directional features, and a new stroke matching method is used for the other kind of feature. Besides, an improved classifier structure is performed to save the time to 50%.There are 2000 different Chinese characters as training samples and testing samples, each character has 6 samples. They are divided into two classes according to their styles. The testing results show that the correct rate of the first class is 90% and the second class is 85%.