Seales, W. Brent

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  • Publication
    The Digital Compilation and Restoration of Herculaneum Fragment P.Herc.118
    (2022-06-10) Chapman, Christy Y; Parker, C. S; Bertelsman, Ali; Gessel, Kristina; Hatch, Hannah; Seevers, Kyra; Brusuelas, James H; Parsons, Stephen; Seales, Brent
    Ancient documents pose many challenges for the scholars who painstakingly study and elucidate them. Natural deterioration occurs over time, erasing words and sentences that were once apparent. Water and fire damage can render text completely unreadable. Wrinkles and folds obscure content essential to meaning. Thankfully, old and new imaging methods can today be combined to rescue “lost” text and make it once again accessible to scholars. Using computer vision techniques like registration, historical images that often represent the most faithful record of the original content of a document can now be combined with those produced by newer technologies, like spectral imaging and 3D modeling. The result is a diachronic digital compilation that enables new scholarly discoveries. Using the collection of fragments from an opened ancient scroll from Herculaneum, PHerc.118, the work outlined in this paper prototypes a process that capitalizes on the best of old and new images to create a single, definitive digital model for scholarly study.
  • Publication
    The St. Chad Gospels: Diachronic Manuscript Registration and Visualization
    (2019-01-08) Parsons, Stephen; Parker, C. Seth; Seales, W. Brent
    This paper presents a software framework for the registration and visualization of layered image sets. To demonstrate the utility of these tools, we apply them to the St. Chad Gospels manuscript, relying on images of each page of the document as it appeared over time. An automated pipeline is used to perform non-rigid registration on each series of images. To visualize the differences between copies of the same page, a registered image viewer is constructed that enables direct comparisons of registered images. The registration pipeline and viewer for the resulting aligned images are generalized for use with other data sets.