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A Novel Rough Set based Technique for Character Spotting on Inscription Images

机译:基于概述题字图像字符斑点的新型粗糙集技术

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The ability to spot a few known characters or symbols allows the linguists and historians to guess the era in which an inscription was made. Manual spotting of these characters proves to be very laborious and error-prone. Hence, automation in character spotting has evolved in recent time, which has its own challenges due to natural wear and tear of inscriptions through aging. In this paper, we present a computationally efficient technique for character spotting using certain concepts from rough set theory. After image binarization, we compute various attributes for the isolated symbols within the ambit of rough set. In order to spot a symbol in the inscription, the corresponding attribute set for the query symbol is matched with that of the inscribed symbols. We provide the details of the method in this paper and show that the symbols or characters can be quite accurately spotted in the inscription.
机译:发现一些已知的角色或符号的能力允许语言学家和历史学家猜测铭文的时代。手动发现这些字符被证明是非常费力和容易出错的。因此,近来时,特征斑点的自动化已经发展,这有由于衰老的自然磨损和铭文的撕裂,这有自己的挑战。在本文中,我们介绍了使用粗糙集理论的某些概念的特定概念的计算有效技术。在图像二值化之后,我们计算粗糙集的范围内的孤立符号的各种属性。为了发现铭文中的符号,为查询符号设置的相应属性设置与刻录符号的相应属性。我们在本文中提供了该方法的细节,并表明符号或字符可以在题字中非常精确地发现。

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