Improvements in Handwritten and Printed Text Separation in Historical Archival Documents

Mahsa Vafaie, J. Waitelonis, H. Sack
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Abstract

The presence of handwritten text and annotations combined with typewritten and machine-printed text in historical archival records make them visually complex, posing challenges for OCR systems in accurately transcribing their content. This paper is an extension of [1], reporting on improvements in the separation of handwritten text from machine-printed text (including typewriters), by the use of FCN-based models trained on datasets created from different data synthesis pipelines. Results show a significant increase of about 20% in the intrinsic evaluation on artificial test sets
历史档案文献手写体与印刷体文本分离的改进
历史档案记录中手写文本和注释与打字和机器打印文本相结合,使其在视觉上变得复杂,这对OCR系统准确转录其内容提出了挑战。本文是[1]的扩展,报告了通过使用基于FCN的模型,在不同数据合成管道创建的数据集上训练,改进了手写文本与机器打印文本(包括打字机)的分离。结果显示,人工测试集的内在评估显著提高了约20%
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