  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.
