Segmenting Dead Sea Scroll Fragments for a Scientific Image Set
This addresses the lack of standardized datasets and methods for manuscript fragment segmentation, enabling more reliable research in this domain-specific area.
The paper tackles the problem of segmenting Dead Sea Scroll fragments from scientific images by developing a customized four-step pipeline to handle challenges like rulers and black backgrounds, and creates a publicly available dataset with ground truth for evaluation.
This paper presents a customized pipeline for segmenting manuscript fragments from images curated by the Israel Antiquities Authority (IAA). The images present challenges for standard segmentation methods due to the presence of the ruler, color, and plate number bars, as well as a black background that resembles the ink and varying backing substrates. The proposed pipeline, consisting of four steps, addresses these challenges by isolating and solving each difficulty using custom tailored methods. Further, the usage of a multi-step pipeline will surely be helpful from a conceptual standpoint for other image segmentation projects that encounter problems that have proven intractable when applying any of the more commonly used segmentation techniques. In addition, we create a dataset with bar detection and fragment segmentation ground truth and evaluate the pipeline steps qualitatively and quantitatively on it. This dataset is publicly available to support the development of the field. It aims to address the lack of standard sets of fragment images and evaluation metrics and enable researchers to evaluate their methods in a reliable and reproducible manner.