Abstract
The objective of our work is to enable the reading of fragile scrolled historical parchments without the need to physically unravel them, thus providing valuable information to a wide range of scholarly disciplines. This problem has not been investigated by the computer vision community properly yet due to the need for parchment scanning technology: standard X-ray equipment is not sufficient as there is a requirement to extract out parchment ink in addition to the parchment's underlying structure. Effective data recovery is also compromised as content from historical scrolled documents is inaccessible due to the deterioration of the parchment. We create a 3D volumetric model of a scrolled parchment's underlying geometry and perform digital unwrapping of the parchment, producing a readable image of the text as an output. The proposed recovery framework consists of structure preserving anisotropic filtering in combination with robust segmentation, surface modelling and ink projection. We demonstrate with real examples how our algorithm is able to recover the underlying text and to solve the major challenge for scrolled parchment analysis, namely segmentation of connected layers and processing the data without user interaction.
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