Performance improvement of the offline cursive style character recognition system

在这项研究中，我们为那些不具备阅读古代文献专业知识的人开发了一个支持系统。由于古代文献多为墨书、草书，这些因素造成了阅读理解上的困难。在该系统中，它显示了从第一到第五个字符的建议，以确定古代文献的字符是现代字符。由于草书字体具有多种形式，并且字符之间只有一行连续拼写，因此开发了一种新颖的算法。通过在数据库中包含“hentai”字符，该系统可以应用于许多字符。此外，使用像素密度的导数来切割草书风格的字符。结果，识别率达到了75%。

In this study, we develop a support system for people who do not have the expert knowledge to read ancient documents. Because of the ancient documents are usually written in India ink and in cursive style, these factors make it difficult reading comprehension. In this system, It displays suggestions of characters up to the first to fifth to determine the character of ancient documents is which of the modern character. A novel algorithm is developed cause of cthe cursive style characters have a various forms and spell out in succession with a single line between characters. The system can be applied to a number of characters by including "hentai" characters in the database. Furthermore cursive style characters were cut using the derivatives of the pixel density. As the result, recognition rate has been achieved 75 percent.