The St. Chad Gospels: Diachronic Manuscript Registration and Visualization

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

Flattening of 3D data

The digital library project strives to digitise special collections of libraries; this consists in storing as binary data, photographs of the content of ancient or rare manuscripts. The object is typically not in a flat plane. One collects, along with the photograph of the unflattened object (and the inevitably distorted text), a positional reading of its surface using laserometer. It is then a mathematical problem of how to use the latter information to undo the distortion of the photograph before storing the digitised image. We discuss a variational formulation and implementation of thi

EduceLab-Scrolls: Verifiable Recovery of Text from Herculaneum Papyri using X-ray CT

We present a complete software pipeline for revealing the hidden texts of the Herculaneum papyri using X-ray CT images. This enhanced virtual unwrapping pipeline combines machine learning with a novel geometric framework linking 3D and 2D images. We also present EduceLab-Scrolls, a comprehensive open dataset representing two decades of research effort on this problem. EduceLab-Scrolls contains a set of volumetric X-ray CT images of both small fragments and intact, rolled scrolls. The dataset also contains 2D image labels that are used in the supervised training of an ink detection model. Labeling is enabled by aligning spectral photography of scroll fragments with X-ray CT images of the same fragments, thus creating a machine-learnable mapping between image spaces and modalities. This alignment permits supervised learning for the detection of "invisible" carbon ink in X-ray CT, a task that is "impossible" even for human expert labelers. To our knowledge, this is the first aligned dataset of its kind and is the largest dataset ever released in the heritage domain. Our method is capable of revealing accurate lines of text on scroll fragments with known ground truth. Revealed text is verified using visual confirmation, quantitative image metrics, and scholarly review. EduceLab-Scrolls has also enabled the discovery, for the first time, of hidden texts from the Herculaneum papyri, which we present here. We anticipate that the EduceLab-Scrolls dataset will generate more textual discovery as research continues

From Damage to Discovery Via Virtual Unwrapping: Reading the Scroll from En-Gedi

Computer imaging techniques are commonly used to preserve and share readable manuscripts, but capturing writing locked away in ancient, deteriorated documents poses an entirely different challenge. This software pipeline—referred to as “virtual unwrapping”—allows textual artifacts to be read completely and noninvasively. The systematic digital analysis of the extremely fragile En-Gedi scroll (the oldest Pentateuchal scroll in Hebrew outside of the Dead Sea Scrolls) reveals the writing hidden on its untouchable, disintegrating sheets. Our approach for recovering substantial ink-based text from a damaged object results in readable columns at such high quality that serious critical textual analysis can occur. Hence, this work creates a new pathway for subsequent textual discoveries buried within the confines of damaged materials

Measuring Time-To-Contact Using Active Camera Control

. In this paper we use a simple, active-camera model to estimate the time-to-contact (TTC) of a moving object. We estimate TTC by enforcing a "uniform scale" constraint on the moving object. By actively adjusting the focal length of the pinhole model, the projected object maintains a fixed image scale regardless of its motion. These adjustments on the ideal pinhole focal length are translated into changes of the actual zoom and focus settings of a real camera system. We obtain improvements over a fixed-camera approach because the scale adjustment (zoom) improves image divergence measurements. We show experimental results indicating that our active method can reduce errors over a larger distance range than fixed-camera methods of estimating time-to-contact. 1 Introduction The intent of active camera control is almost always to create additional constraints and more favorable imaging situations. Extrinsic parameters, which control the position and orientation of the camera, determine th..

Digital Unwrapping: Homer, Herculaneum, and the Scroll from En-Gedi

Progress over the past fifteen years in the digitization and analysis of text found in cultural objects (inscriptions, manuscripts, scrolls) has led this past year to a new and astonishing discovery. This talk will tell the story of emerging methods for imaging and analysis culminating in a personal account of the discovery, the people involved, and the technical approaches used. The digitization of damaged objects supports a new era of collaboration and exploration that has enabled compelling new discoveries and solutions to long-standing problems

Interpreting Music Manuscripts: A Logic-Based, Object-Oriented Approach

This paper presents a complete framework for recognizing classes of machine-printed musical manuscripts. Our framework is designed around the decomposition of a manuscript into objects such as staves and bars which are processed with a knowledge base module that encodes rules in Prolog. Object decomposition focuses the recognition problem, and the rule base provides a powerful and flexible way to encode the rules of a particular manuscript class. Our rule-base registers notes and stems, eliminates false-positives and correctly labels notes according to their position on the staff. We present results that show 99% accuracy at detecting note-heads and 95% accuracy in finding stems. Figure 1: (top) This is a single staff from a manuscript to be interpreted. (bottom) The result of our tool finding notes, beams and stems. 1 Introduction The goal of music manuscript analysis is to obtain a complete representation of a musical document given only a digital image. The form of this recovered..

Y.: Digital restoration using volumetric scanning

ABSTRACT In this paper we present a new, nondestructive method for revealing inaccessible text buried within damaged books and scrolls. The method is based on volumetric scanning followed by data modeling and physically-based simulation. We show by experiment that it is possible to recover readable text from objects without physically opening or damaging them. In handling damaged collections, conservators often face a choice between two frustrating alternatives: indefinite preservation without analysis, or irreversible physical harm for the sake of potential discovery. We believe that this work creates a new opportunity that embraces both the need to preserve and the possibility for complete analysis