Scholarlink

<p>In several manuscripts, text is obscured due to glued together leaves, making it difficult or impossible to read. In this context, this study explores the use of reflectance and transmittance imaging spectroscopy (RIS and TIS) in the visible and near-infrared range (400–1000 nm) to recover hidden texts. The method is applied to two cases of medieval Frisian legal codes from the Richthofen Collection, where we employed Non-Negative Matrix Factorization (NMF) for the analysis of single and spectrally fused datasets integrating both RIS and TIS. We further integrated spatial stitching of adjacent areas to enhance spatial resolution of the images. Our results demonstrate that factorization algorithms perform well on fused datasets, with spectral fusion proving essential in complex cases where individual analyses fail to clearly reveal hidden text.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Unveiling hidden text in Frisian historic manuscripts by fused reflectance and transmittance imaging spectroscopy

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月12日

查看全文
  • Alessia Di Benedetto,
  • Luìs Manuel de Almieda Nieto,
  • Daniel Marsh,
  • Janneke Zwetsloot,
  • Riemer Janssen,
  • Anne Tjerk Popkema,
  • Herre de Vries,
  • Daniela Comelli,
  • Matthias Alfeld

摘要

In several manuscripts, text is obscured due to glued together leaves, making it difficult or impossible to read. In this context, this study explores the use of reflectance and transmittance imaging spectroscopy (RIS and TIS) in the visible and near-infrared range (400–1000 nm) to recover hidden texts. The method is applied to two cases of medieval Frisian legal codes from the Richthofen Collection, where we employed Non-Negative Matrix Factorization (NMF) for the analysis of single and spectrally fused datasets integrating both RIS and TIS. We further integrated spatial stitching of adjacent areas to enhance spatial resolution of the images. Our results demonstrate that factorization algorithms perform well on fused datasets, with spectral fusion proving essential in complex cases where individual analyses fail to clearly reveal hidden text.