Research On Chinese Handwritten Character Recognition

The problem of Chinese handwritten character recognition by computer is thought of one of the most difficult problems in the field of pattern recognition. In our project of "Computer Chinese Handwriting Identification" and "Chinese Handwriting Sort in Internet", we always need to pick some special hand script from the manuscript for discrimination. But this work is very troublesome, uninteresting and easy to make mistakes. To improve the automation and intelligence of the software, we need to implement the function of auto-pick scripts. That is the task of handwritten character recognition. But the problem is too large and difficult to be solved all. Even though, in our research, we just want to pick a small quantity of special characters from the manuscript. It supplies us a possibility to solve the problem successfully.The main research content of this thesis include: the basic theory and method of character recognition, the pre-work of script image, the classification algorithm, the research of neutral network, and the system design of usual character recognition.The thesis introduces two basic thinking in field of optic character recognition (OCR), which is statistical- decision algorithm based on math characteristic of character and structure-decomposition algorithm based on physical characteristic of character. The thesis introduced 6 steps of OCR pre-work, which is getting rid of noise, image binary, image incline rectify, image incise, image standardize and image thinning, the classification algorithm include rude classification and particular classification. We adopt two differentcharacteristic extracting methods and recognition algorithms accordingly. Thirdly, we researched the neutral network algorithm and its improvement algorithm, designed a BP neutral network, which could apply in Chinese handwritten recognition. In the network, the input node is 64, the middle is 20 and the output is 4.we also use matlab train and simulate the designed network. Finally, we designed software, which combines all the correlate theory and method list above to validate the thinking.In this project, a new handwritten character recognition system has been designed successfully, which has 3 levels. In the first level, it used the tradition periphery characteristic to class approximately. In the second level, it used stressful grids characteristic to class accurately and in the third level, used neutral network tools and gives the last output.The software uses Delphi 6.0 do experiments, from the effect of experiment. We could see, its correct recognition rate has reach up to 98 %( 10 candidates) this result is satisfying and encouraging.