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- Title
A deep image segmentation‐based method for stitching ancient‐book images without an overlapping region.
- Authors
Chen, Genlang; Zhou, Han; Huang, Gang; Song, Guanghui; Zhang, Jiajian
- Abstract
With continuous advancements in ancient‐book digitization and preservation research, the problems with the stitching of ancient‐book images have become increasingly prominent, as traditional feature‐mapping‐based methods cannot satisfactorily stitch non‐overlapping images. To realize the accurate stitching of the left and right pages of ancient‐book images, this paper proposes a method for ancient‐book image stitching to meet the requirements of their digitization in back‐wrapped binding and other binding forms. First, a dataset of the black text frames from ancient‐book images was established and then used to train a VGG16‐UNet network for the extraction of black text frames. Then, the Douglas–Peucker algorithm was used to fit the black text frames and filter outliers. Finally, a sliding matching algorithm based on the position information of black text frames was proposed for the rectification of misalignments. The results showed that the method achieved a satisfying stitching effect and had good robustness.
- Subjects
IMAGE segmentation; TEXT recognition; DIGITIZATION
- Publication
IET Image Processing (Wiley-Blackwell), 2023, Vol 17, Issue 10, p3068
- ISSN
1751-9659
- Publication type
Article
- DOI
10.1049/ipr2.12856