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A systematic feature selection process for a Sinhala character recognition system

机译:僧伽罗语字符识别系统的系统特征选择过程

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Optical Character Recognition (OCR) is a well-researched topic. Feature selection plays a vital role in a functional OCR system. The right feature selection process would make an OCR system faster, accurate and complete. The Sinhala language suffers from complete OCR systems. In this paper, we introduce a quantifiable, and systematic feature selection process for OCR systems. Using which, we show that the feature set that usually works well with English characters will not work for Sinhala letters. Further, we examine and compare some existing features in the literature and also introduce new features that would work well for Sinhala letter. We argue that the features we have identified and introduced would help researchers to make the best and complete OCR system for Sinhala.
机译:光学字符识别(OCR)是一个经过充分研究的主题。功能选择在功能性OCR系统中起着至关重要的作用。正确的功能选择过程将使OCR系统更快,更准确,更完整。僧伽罗语语言拥有完整的OCR系统。在本文中,我们介绍了一种用于OCR系统的可量化且系统的特征选择过程。使用它,我们表明通常与英语字符配合使用的功能集不适用于僧伽罗字母。此外,我们检查和比较了文献中的一些现有功能,并介绍了适用于僧伽罗字母的新功能。我们认为,我们已经确定和引入的功能将有助于研究人员为Sinhala制作最佳和完整的OCR系统。

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