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A Geometric Feature-Based Algorithm for the Virtual Reading of Closed Historical Manuscripts
Rosa Brancaccio1, Fauzia Albertin2, Marco Seracini1
1Department of Physics and Astronomy "Augusto Righi", University of Bologna, 6/2, Viale Carlo Berti Pichat, 40127 Bologna, Italy.
Journal of Imaging
|October 27, 2023
Summary
This study introduces a novel method using X-ray Computed Tomography (CT) to digitally preserve fragile ancient manuscripts. The technique effectively segments individual pages from 3D CT scans, aiding in document preservation.
Area of Science:
- Digital Humanities
- Cultural Heritage Preservation
- Medical Imaging Applications
Background:
- Traditional document scanning is inadequate for fragile, ancient manuscripts.
- Digitizing historical documents presents significant challenges for conservators.
- X-ray Computed Tomography (CT) shows promise for data acquisition from such documents.
Purpose of the Study:
- To develop a new procedure for segmenting single pages from 3D CT data of closed historical manuscripts.
- To overcome the challenges in extracting readable pages from tomographic images.
- To enhance the digitization and preservation of ancient handwritten documents.
Main Methods:
- Utilizing X-ray Computed Tomography (CT) for 3D data acquisition of closed manuscripts.
- Developing a novel segmentation algorithm based on geometric features.
- Applying flood fill methods for precise page separation within the CT volume.
Main Results:
- Successfully segmented individual pages from 3D tomographic data of historical manuscripts.
- Demonstrated the capability of the proposed methodology in separating distinct pages.
- The results confirm the effectiveness of the algorithm in processing complex CT volumes.
Conclusions:
- The proposed procedure offers a viable solution for segmenting pages from CT scans of historical manuscripts.
- This technique advances the digital preservation of fragile cultural heritage.
- Further development can improve the extraction and reading of ancient documents.
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