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Robust virtual unrolling of historical parchment XMT images

Liu, Chang, Rosin, Paul L. ORCID:, Lai, Yu-Kun ORCID: and Hu, Weiduo 2018. Robust virtual unrolling of historical parchment XMT images. IEEE Transactions on Image Processing 27 (4) , pp. 1914-1926. 10.1109/TIP.2017.2783626

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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.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Additional Information: This work is licensed under a Creative Commons Attribution 3.0 License
Publisher: IEEE
ISSN: 1057-7149
Date of First Compliant Deposit: 25 January 2018
Date of Acceptance: 11 December 2017
Last Modified: 22 Sep 2023 21:24

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