Extraction of features is critical to improve the recognition rate of off-line handwritten characters.
要提高脱机手写字符识别的识别率，关键是特征的提取。
Off-line handwritten Chinese characters recognition is a popular research point in pattern recognition field, and it can be widely used in many areas.
脱机手写体汉字识别是当前模式识别领域的一个研究热点，具有广泛的应用前景。
This thesis mainly finishes the following work in the field of off-line handwritten Chinese characters' feature extracting and auto-recognition.
本文主要在汉字字符的特征提取和自动识别方面做了如下的工作。
The research on giving verification of the electronic signature in Chinese characters belongs to the research on the verification of the special off-line handwritten Chinese characters.
中文电子签名的认证方法研究可归属于特定人脱机手写汉字识别研究的范畴。
Then makes a summary of various classifiers and ensemble methods commonly used in the off-line handwritten Chinese characters recognition.
然后对脱机手写体汉字识别中常用的分类器以及集成方法进行了认真的学习和总结。
Similar characters are common among Chinese characters, which is a main reason for affecting the recognition rate of off -line handwritten Chinese character.
相似字的普遍存在是影响脱机手写体汉字识别率低的主要原因之一。
Segmentation of off-line handwritten Chinese characters is the premise of recognition. It is most difficult to segment connected characters.
离线手写汉字的切分是识别的前提，其中粘连手写汉字的切分最为困难。
The research on off-line handwritten Chinese characters machine recognition has not only important theoretical value, but also wide market prospect.
脱机手写体汉字的识别不仅具有重要的理论研究价值，而且具有广阔的市场前景。
The research on off-line handwritten Chinese characters machine recognition has not only important theoretical value, but also wide market prospect.
脱机手写体汉字的识别不仅具有重要的理论研究价值，而且具有广阔的市场前景。
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