基于中心距离特征的在线维吾尔文字识别技术研究

Wujiahemaiti Simayi, Mayire Ibrayim, Dilmurat Tursun, A. Hamdulla
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引用次数: 7

摘要

本文提出了中心距离特征(CDF)作为在线维吾尔语手写字符识别的一种有效方法。在前期研究的基础上,利用中心距离特征(center distance feature,简称CDF)对在线维吾尔语手写字符识别进行了进一步的研究。本文介绍了中心距离特征的提取及其CDF-2、CDF-4和CDF-8三种不同的方法,对维吾尔语32种孤立形式的平均识别准确率分别提高到78.17%、90.47%和94.50%。来自400位不同作家的12800个样本参与了实验。该系统使用总样本的70%进行训练,并对剩余的30%进行测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on on-line Uyghur character recognition technology based on center distance feature
In this paper, the center distance feature (CDF) is presented as an efficient approach for on-line Uyghur handwritten character recognition. Based on early research for on-line Uyghur handwritten character recognition, a further research is conducted with center distance feature, abbreviated as CDF. This paper introduces the extraction of center distance feature and its three different methods such as CDF-2, CDF-4 and CDF-8 which have improved the average recognition accuracy respectively to 78.17%, 90.47% and 94.50% for the 32 isolated forms of Uyghur characters. 12800 samples from 400 different writers are participated into experiments. The system is trained using 70 percent of total samples and tested on the remained 30 percent.
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