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Detecting Text Areas and Decorative Elements in Ancient Manuscripts

机译:探测古代手稿中的文本区域和装饰元素

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An approach for the detection of decorative elements – such as initials and headlines – and text regions, focused on ancient manuscripts, is presented. Due to their age, ancient manuscripts suffer from degradation and staining as well as ink is faded-out over the time. Identifying decorative elements and text regions allows indexing a manuscript and serves as input for Optical Character Recognition (OCR) as it localizes regions of interest within document pages. We propose a robust method inspired by state-of-the-art object recognition methodologies. Scale Invariant Feature Transform (SIFT) descriptors are chosen to detect the regions of interest, and the scale of the interest points is used for localization. The classification is based on the fact that local properties of the decorative elements are different to those of regular text. The results show that the method is able to locate regular text in ancient manuscripts. The detection rate of decorative elements is not as high as for regular text but already yields to promising results.
机译:提出了一种检测装饰元素的方法 - 例如初始和头条新闻和文本区域,专注于古代稿件。由于他们的年龄,古代稿件遭受退化和染色以及墨水随着时间的推移。识别装饰元素和文本区域允许索引稿件,并用作光学字符识别(OCR)的输入,因为它本地化文档页面内的感兴趣区域。我们提出了一种受到最先进的对象识别方法的强大方法。选择规模不变特征变换(SIFT)描述符以检测感兴趣的区域,并且兴趣点的比例用于本地化。分类基于装饰元素的本地属性与常规文本的本地属性不同。结果表明,该方法能够在古代稿件中定位常规文本。装饰元素的检出率并不像常规文本那么高,但已经产生了有希望的结果。

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