Semi-automatic Solving of "Jigsaw puzzles" for Material Reconstruction of Dead Sea Scrolls

Digital solving of jigsaw puzzles have been well researched throughout the years and multiple approaches to solve them have been proposed. But these approaches have not been applied to reconstructing ancient manuscripts out of transient material such as leather or parchment. The literature describes ways to reconstruct ancient artefacts but they describe the process for more durable objects like pottery. In this thesis we explore the usability of the existing state-of-the-art methods for the purpose of aiding reconstructing of the Dead Sea Scrolls, also known as Qumran scrolls. Our experiments show that the existing methods as such do not provide good results in this domain, but with modifications provide help through a semi-automated reconstruction process. We expect these modifications and the software that was created as a by-product of this thesis to ease the researchers' work by automating the previously laborious manual work

Optimization for automated assembly of puzzles

The puzzle assembly problem has many application areas such as restoration and reconstruction of archeological findings, repairing of broken objects, solving jigsaw type puzzles, molecular docking problem, etc. The puzzle pieces usually include not only geometrical shape information but also visual information such as texture, color, and continuity of lines. This paper presents a new approach to the puzzle assembly problem that is based on using textural features and geometrical constraints. The texture of a band outside the border of pieces is predicted by inpainting and texture synthesis methods. Feature values are derived from these original and predicted images of pieces. An affinity measure of corresponding pieces is defined and alignment of the puzzle pieces is formulated as an optimization problem where the optimum assembly of the pieces is achieved by maximizing the total affinity measure. An fft based image registration technique is used to speed up the alignment of the pieces. Experimental results are presented on real and artificial data sets

A texture based approach to reconstruction of archaeological finds

Reconstruction of archaeological finds from fragments, is a tedious task requiring many hours of work from the archaeologists and restoration personnel. In this paper we present a framework for the full reconstruction of the original objects using texture and surface design information on the sherd. The texture of a band outside the border of pieces is predicted by inpainting and texture synthesis methods. The confidence of this process is also defined. Feature values are derived from these original and predicted images of pieces. A combination of the feature and confidence values is used to generate an affinity measure of corresponding pieces. The optimization of total affinity gives the best assembly of the piece. Experimental results are presented on real and artificial data

Batch-based Model Registration for Fast 3D Sherd Reconstruction

3D reconstruction techniques have widely been used for digital documentation of archaeological fragments. However, efficient digital capture of fragments remains as a challenge. In this work, we aim to develop a portable, high-throughput, and accurate reconstruction system for efficient digitization of fragments excavated in archaeological sites. To realize high-throughput digitization of large numbers of objects, an effective strategy is to perform scanning and reconstruction in batches. However, effective batch-based scanning and reconstruction face two key challenges: 1) how to correlate partial scans of the same object from multiple batch scans, and 2) how to register and reconstruct complete models from partial scans that exhibit only small overlaps. To tackle these two challenges, we develop a new batch-based matching algorithm that pairs the front and back sides of the fragments, and a new Bilateral Boundary ICP algorithm that can register partial scans sharing very narrow overlapping regions. Extensive validation in labs and testing in excavation sites demonstrate that these designs enable efficient batch-based scanning for fragments. We show that such a batch-based scanning and reconstruction pipeline can have immediate applications on digitizing sherds in archaeological excavations. Our project page: https://jiepengwang.github.io/FIRES/.Comment: Project page: https://jiepengwang.github.io/FIRES

FIRES: Fast Imaging and 3D Reconstruction of Archaeological Sherds

Sherds, as the most common artifacts uncovered during archaeologicalexcavations, carry rich information about past human societies so need to beaccurately reconstructed and recorded digitally for analysis and preservation.Often hundreds of fragments are uncovered in a day at an archaeologicalexcavation site, far beyond the scanning capacity of existing imaging systems.Hence, there is high demand for a desirable image acquisition system capable ofimaging hundreds of fragments per day. In response to this demand, we developeda new system, dubbed FIRES, for Fast Imaging and 3D REconstruction of Sherds.The FIRES system consists of two main components. The first is an optimallydesigned fast image acquisition device capable of capturing over 700 sherds perday (in 8 working hours) in actual tests at an excavation site, which is oneorder-of-magnitude faster than existing systems. The second component is anautomatic pipeline for 3D reconstruction of the sherds from the images capturedby the imaging acquisition system, achieving reconstruction accuracy of 0.16milimeters. The pipeline includes a novel batch matching algorithm that matchespartial 3D scans of the front and back sides of the sherds and a new ICP-typemethod that registers the front and back sides sharing very narrow overlappingregions. Extensive validation in labs and testing in excavation sitesdemonstrated that our FIRES system provides the first fast, accurate, portal,and cost-effective solution for the task of imaging and 3D reconstruction ofsherds in archaeological excavations.<br

Escherichia coli low-copy-number plasmid R1 centromere parC forms a U-shaped complex with its binding protein ParR

The Escherichia coli low-copy-number plasmid R1 contains a segregation machinery composed of parC, ParR and parM. The R1 centromere-like site parC contains two separate sets of repeats. By atomic force microscopy (AFM) we show here that ParR molecules bind to each of the 5-fold repeated iterons separately with the intervening sequence unbound by ParR. The two ParR protein complexes on parC do not complex with each other. ParR binds with a stoichiometry of about one ParR dimer per each single iteron. The measured DNA fragment lengths agreed with B-form DNA and each of the two parC 5-fold interon DNA stretches adopts a linear path in its complex with ParR. However, the overall parC/ParR complex with both iteron repeats bound by ParR forms an overall U-shaped structure: the DNA folds back on itself nearly completely, including an angle of ∼150°. Analysing linear DNA fragments, we never observed dimerized ParR complexes on one parC DNA molecule (intramolecular) nor a dimerization between ParR complexes bound to two different parC DNA molecules (intermolecular). This bacterial segrosome is compared to other bacterial segregation complexes. We speculate that partition complexes might have a similar overall structural organization and, at least in part, common functional properties