32 research outputs found
From Invisibility to Readability: Recovering the Ink of Herculaneum
The noninvasive digital restoration of ancient texts written in carbon black ink and hidden inside artifacts has proven elusive, even with advanced imaging techniques like x-ray-based micro-computed tomography (micro-CT). This paper identifies a crucial mistaken assumption: that micro-CT data fails to capture any information representing the presence of carbon ink. Instead, we show new experiments indicating a subtle but detectable signature from carbon ink in micro-CT. We demonstrate a new computational approach that captures, enhances, and makes visible the characteristic signature created by carbon ink in micro-CT. This previously unseen evidence of carbon inks, which can now successfully be made visible, is a discovery that can lead directly to the noninvasive digital recovery of the lost texts of Herculaneum
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
XRF Ink Analysis of Selected Fragments from the Herculaneum Collection of the Biblioteca Nazionale di Napoli
The most commonly used ink in antiquity was carbon-based, and the main element of carbonized papyrus is carbon, making conventional computed tomography (CT-scanning) of Herculaneum scrolls difficult. However, Roman and Greek inks containing metals have recently been identified in some papyri from Egypt, changing our understanding of ink technology in antiquity. This raises hope that some rolls can be virtually unrolled by CT-scanning. Here we present the results of a preliminary analysis, aimed at identifying scrolls whose ink contains metals
Weakly Supervised Geodesic Segmentation of Egyptian Mummy CT Scans
In this paper, we tackle the task of automatically analyzing 3D volumetric
scans obtained from computed tomography (CT) devices. In particular, we address
a particular task for which data is very limited: the segmentation of ancient
Egyptian mummies CT scans. We aim at digitally unwrapping the mummy and
identify different segments such as body, bandages and jewelry. The problem is
complex because of the lack of annotated data for the different semantic
regions to segment, thus discouraging the use of strongly supervised
approaches. We, therefore, propose a weakly supervised and efficient
interactive segmentation method to solve this challenging problem. After
segmenting the wrapped mummy from its exterior region using histogram analysis
and template matching, we first design a voxel distance measure to find an
approximate solution for the body and bandage segments. Here, we use geodesic
distances since voxel features as well as spatial relationship among voxels is
incorporated in this measure. Next, we refine the solution using a GrabCut
based segmentation together with a tracking method on the slices of the scan
that assigns labels to different regions in the volume, using limited
supervision in the form of scribbles drawn by the user. The efficiency of the
proposed method is demonstrated using visualizations and validated through
quantitative measures and qualitative unwrapping of the mummy
LOOKING INSIDE VOTIVE CREATURES: COMPUTED TOMOGRAPHY (CT) SCANNING OF ANCIENT EGYPTIAN MUMMIFIED ANIMALS IN IZIKO MUSEUMS OF SOUTH AFRICA: A PRELIMINARY REPORT
The ancient Egyptians mummified many more animals than humans.
The study of ancient Egyptian animal mummies is varied and
extensive. Currently new methodologies and modern technology are
being used to unlock the secrets of animal mummies. Recently five
animal mummies housed in the Egyptian collection of Iziko
Museums of South Africa in Cape Town were scanned using a state
of the art computed tomography (CT) scanner at Stellenbosch
University. Preliminary results revealed two complete bird skeletons,
a claw, a fake and the partial skeleton of what appears to be a cat
A Local Iterative Approach for the Extraction of 2D Manifolds from Strongly Curved and Folded Thin-Layer Structures
Ridge surfaces represent important features for the analysis of 3-dimensional
(3D) datasets in diverse applications and are often derived from varying
underlying data including flow fields, geological fault data, and point data,
but they can also be present in the original scalar images acquired using a
plethora of imaging techniques. Our work is motivated by the analysis of image
data acquired using micro-computed tomography (Micro-CT) of ancient, rolled and
folded thin-layer structures such as papyrus, parchment, and paper as well as
silver and lead sheets. From these documents we know that they are
2-dimensional (2D) in nature. Hence, we are particularly interested in
reconstructing 2D manifolds that approximate the document's structure. The
image data from which we want to reconstruct the 2D manifolds are often very
noisy and represent folded, densely-layered structures with many artifacts,
such as ruptures or layer splitting and merging. Previous ridge-surface
extraction methods fail to extract the desired 2D manifold for such challenging
data. We have therefore developed a novel method to extract 2D manifolds. The
proposed method uses a local fast marching scheme in combination with a
separation of the region covered by fast marching into two sub-regions. The 2D
manifold of interest is then extracted as the surface separating the two
sub-regions. The local scheme can be applied for both automatic propagation as
well as interactive analysis. We demonstrate the applicability and robustness
of our method on both artificial data as well as real-world data including
folded silver and papyrus sheets.Comment: 16 pages, 21 figures, to be published in IEEE Transactions on
Visualization and Computer Graphic
Revisiting the Jerash Silver Scroll: A new visual data analysis approach
This article revisits a complexly folded silver scroll excavated in Jerash, Jordan, in 2014 that was digitally examined in 2015. In this article we apply, examine and discuss a new virtual unfolding technique that results in a clearer image of the scroll's 17 lines of writing. We also compare it to the earlier unfolding and discuss progress in general analytical tools. We publish the original and the new images as well as the unfolded volume data open access in order to make these available to researchers interested in optimising unfolding processes of various complexly folded materials