Robust virtual unrolling of historical parchment XMT images

We develop a framework to virtually unroll fragile historical parchment scrolls, which cannot be physically unfolded via a sequence of X-ray tomographic slices, thus providing easy access to those parchments whose contents have remained hidden for centuries. The first step is to produce a topologically correct segmentation, which is challenging as the parchment layers vary significantly in thickness, contain substantial interior textures and can often stick together in places. For this purpose, our method starts with linking the broken layers in a slice using the topological structure propagated from its previous processed slice. To ensure topological correctness, we identify fused regions by detecting junction sections, and then match them using global optimization efficiently solved by the blossom algorithm, taking into account the shape energy of curves separating fused layers. The fused layers are then separated using as-parallel-as-possible curves connecting junction section pairs. To flatten the segmented parchment, pixels in different frames need to be put into alignment. This is achieved via a dynamic programming-based global optimization, which minimizes the total matching distances and penalizes stretches. Eventually, the text of the parchment is revealed by ink projection. We demonstrate the effectiveness of our approach using challenging real-world data sets, including the water damaged fifteenth century Bressingham scroll

A Geometric Feature-Based Algorithm for the Virtual Reading of Closed Historical Manuscripts

X-ray Computed Tomography (CT), a commonly used technique in a wide variety of research fields, nowadays represents a unique and powerful procedure to discover, reveal and preserve a fundamental part of our patrimony: ancient handwritten documents. For modern and well-preserved ones, traditional document scanning systems are suitable for their correct digitization, and, consequently, for their preservation; however, the digitization of ancient, fragile and damaged manuscripts is still a formidable challenge for conservators. The X-ray tomographic approach has already proven its effectiveness in data acquisition, but the algorithmic steps from tomographic images to real page-by-page extraction and reading are still a difficult undertaking. In this work, we propose a new procedure for the segmentation of single pages from the 3D tomographic data of closed historical manuscripts, based on geometric features and flood fill methods. The achieved results prove the capability of the methodology in segmenting the different pages recorded starting from the whole CT acquired volume

Virtual Recovery of Content from X-Ray Micro-Tomography Scans of Damaged Historic Scrolls

Part of this work was carried out with funding from the EPSRC (project EP/G010110/1, High defnition X-ray microtomography and advanced visualisation techniques for information recovery from unopenable historical documents), the China Postdoctoral Innovation Program (No. 230210342) and the China Scholarship Council (File No. 201406020068