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Handwritten Tamil Character Recognition Using Zernike Moments and Legendre Polynomial

机译:手写的泰米尔字符识别使用Zernike时刻和Legendre多项式

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Optical character recognition systems have been effectively developed for recognizing the printed characters of many non-Indian languages such as English and Chinese. At early stages, few research works were carried out for recognizing the handwritten characters, and now, various efforts are on the way for the development of efficient systems for recognizing the Indian languages, especially for Tamil, a south Indian language widely used in Tamilnadu, Pudhucherry, Singapore, and Srilanka. In this paper, an OCR system is developed for the recognition of basic characters in handwritten Tamil language, which can handle different font sizes and font types. Zernike moments and Legendre polynomial which have been used in pattern recognition are used in this system to extract the features of handwritten Tamil characters. A comparative study is performed in this paper. Feed forward back propagation neural classifier has been used for the classification of Tamil characters.
机译:已经有效地开发了光学字符识别系统,用于识别英语和中文等许多非印度语言的印刷人物。在早期阶段,还有很少的研究作品来识别手写的人物,现在,各种努力正在开发有效系统,以便认识到印度语言,特别是对于在塔米尔纳德广泛使用的南印度语言, Pudhucherry,新加坡和斯里兰卡。在本文中,开发了一个OCR系统,用于识别手写泰米尔语言中的基本字符,可以处理不同的字体大小和字体类型。在该系统中使用了在模式识别中使用的Zernike矩和传奇的多项式,以提取手写泰米尔字符的特征。本文进行了对比研究。馈送前后传播神经分类器已被用于泰米尔字符的分类。

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