Handwritten Recognition of Rajasthani Characters by Classifier SVM

S. E. Warkhede, S. K. Yadav, V. Thakare, P. E. Ajmire
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引用次数: 1

Abstract

The entirely distinct pattern recognition technologies have been proposed over recent years and thus the different research teams focus on the effects of popularity. Because of its use in many areas, such as pattern recognition and machine learning, handwritten character recognition has found great success. In online handwritten character recognition, the basic field is for use. The various character recognition techniques were suggested in the offline handwritten recognition process. Although the techniques for transforming textual content are established by some empirical studies and publications. This textual material has been translated from a paper file into a machine-readable form. The character recognition system could help produce a paperless document as a key in the coming days. The key aspect was the digitization of paper documents and the retrieval of existing paper records as well. In this job, we took out offline samples of some Rajasthani handwritten characters. The proposed average recognition rate for machine archives is 89.82 percent, using histogram oriented gradient features and support vector machine classifiers.
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基于SVM的拉贾斯坦语字符手写识别
近年来,人们提出了截然不同的模式识别技术,因此不同的研究团队关注的是受欢迎程度的影响。由于它在模式识别和机器学习等许多领域的应用,手写字符识别取得了巨大的成功。在在线手写体字符识别中,基本字段是供使用的。在离线手写识别过程中,提出了各种字符识别技术。虽然转换文本内容的技术是由一些实证研究和出版物建立的。这些文本材料已从纸质文件翻译成机器可读的形式。在未来的日子里,字符识别系统可以帮助生产一种无纸化的文件作为钥匙。关键方面是纸质文件的数字化和现有纸质记录的检索。在这项工作中,我们取出了一些拉贾斯坦邦手写字符的离线样本。采用直方图导向梯度特征和支持向量机器分类器,提出的机器档案平均识别率为89.82%。
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