Detecting Text Areas and Decorative Elements in Ancient Manuscripts

A. Garz, Markus Diem, Robert Sablatnig
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引用次数: 16

Abstract

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.
古代手稿文本区域与装饰元素的检测
提出了一种用于检测装饰元素(如首字母和标题)和文本区域的方法,主要针对古代手稿。由于它们的年代久远,古代手稿会随着时间的推移而退化和染色,墨水也会褪色。识别装饰元素和文本区域可以为手稿建立索引,并作为光学字符识别(OCR)的输入,因为它可以在文档页面中定位感兴趣的区域。我们提出了一种鲁棒的方法,灵感来自最先进的目标识别方法。选择尺度不变特征变换(SIFT)描述子检测感兴趣的区域,并利用感兴趣点的尺度进行定位。这种分类是基于装饰元素的局部属性与常规文本的局部属性不同这一事实。结果表明,该方法能够对古代手稿中的规则文本进行定位。虽然装饰元素的检出率不如常规文本高,但已经取得了令人满意的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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