Challenges in Revealing Readable Text from Fragments Hidden in Book Bindings:A Case Study from the Herlufsholm Collection

Abstract

Manuscript fragments repurposed in book bindings contain valuable historical text, yet reading these hidden texts presents significant challenges. Multispectral and hyperspectral imaging (MSI and HSI), followed by spectral unmixing, are commonly used to enhance text visibility. However, additional layers of paper make the recovery process particularly difficult. The resulting text images are often blurry and unrecognizable to both human experts and Optical Character Recognition (OCR) systems. Furthermore, the problem is compounded by the lack of sufficient representative data for training deep learning-based restoration models. In this paper, we systematically examine the challenges of recovering readable text images from bookbinding fragments, with a focus on fragments on Herlufsholm 24.1 as a case study. These fragments are part of the Herlufsholm Collection at the University Library of Southern Denmark. We begin with a comparative analysis of MSI and HSI to evaluate their effectiveness in revealing text, highlighting their respective advantages and limitations. To assess the impact of overlaid materials, we conduct a controlled experiment using artificial samples, capturing hyperspectral images of both covered and uncovered text. Additionally, we analyze blur maps to investigate whether the observed blurriness is uniform and whether common models, such as Gaussian blur, adequately represent it. Finally, we explore the effectiveness of existing deblurring models, identifying key limitations, and discussing potential strategies for improving text readability. This study provides a structured analysis of the obstacles at each stage of the process, from imaging to post-processing and deblurring, offering insight into the best practice for recovering text hidden in bindings.</p