Algorithmic Reconstruction of Broken Fragments

2008

Automatic reconstruction of archeological broken objects is an invaluable tool for restoration purposes and personnel. In this paper, we assume that broken pieces have similar characteristics on their common boundaries, when they are correctly combined. In this paper we work in 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. Feature values are derived from these original and predicted images of pieces. We present a quantitative and qualitative comparison over a large set of features and over a large set of synthetic and real archeological broken objects.

British Machine Vision Conference, 2000

We describe here an efficient algorithm for re-assembling one or more un- known objects that have been broken or torn into a large number of ir- regular fragments—a problem that often arises in achaeology, art restora- tion, forensics, and other disciplines. The algorithm compares the curvature- encoded fragment outlines, using a modified dynamic programming sequence- matching algorithm, at progressively increasing

2010

3D laser scanning of broken cultural heritage content is becoming increasingly popular, resulting in large collections of detailed fractured archeological 3D objects that have to be reassembled virtually. In this paper, we present a new semi-automatic reassembly approach for pairwise matching of the fragments, that makes it possible to take into account both the archeologist's expertise, as well as the power of automatic geometry-driven matching algorithms. Our semi-automatic reassembly approach is based on a real-time interaction loop: an expert user steadily specifies approximate initial relative positions and orientations between two fragments by means of a bimanual tangible user interface. These initial poses are continuously corrected and validated in real-time by an algorithm based on the Iterative Closest Point (ICP): the potential contact surface of the two fragments is identified by efficiently pruning insignificant areas of a pair of two bounding sphere hierarchies, that is combined with a k-d tree for closest vertex queries. The locally optimal relative pose for the best match is robustly estimated by taking into account the distance of the closest vertices as well as their normals. We provide feedback to the user by a visual representation of the locally optimal best match and its associated error. Our first results on a concrete dataset show that our system is capable of assisting an expert user in real-time during the pairwise matching of downsampled 3D fragments.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002

AbstractÐWe describe here an efficient procedure for reassembling unknown two-dimensional objects that have been broken or torn into a large number of irregular fragmentsÐa problem that often arises in archaeology, art restoration, forensics, and other disciplines. The procedure compares the curvature-encoded fragment outlines, at progressively increasing scales of resolution, using an incremental dynamic programming sequence-matching algorithm. The total cost gets reduced by a factor proportional to the mean number of samples per segment, which makes the method viable for problems of practical size (thousands of fragments). The performance of our method is illustrated with an artificial but realistic example.

2011

Artefacts' reconstruction is a fundamental part of conservation and one of the most common remedial conservation activities with great contribution to archaeological research. The manual procedure for fragments' matching is a painstaking, time-and space-consuming operation. As a result the development of working methodologies for digital refitting of fragments is of fundamental importance for archaeological research and conservation practice. This study presents a comparative analysis of manual and digital reconstruction, which has never been explored even if computer scientists have achieved many developments in the field of digital refitting. Results indicate the parallels between manual and digital processes in terms of durability, integrity and practicality. Also, in order to provide methodological directions to conservators, three different semi-automatic fragments matching approaches based on their effectiveness in managing the project and alignment of fragments were used A combined strategy, making use of different pieces of software, is recommended. In addition, the modelling techniques for digital restoration were described along with the uses of the virtually restored artefact. Faenza maiolica, black-glazed, Gnathian and coarse ware ceramics were used as case studies.

2016

Artefacts' reconstruction is a fundamental part of conservation and one of the most common remedial conservation activities with great contribution to archaeological research. The manual procedure for fragments' matching is a painstaking, time- and space-consuming operation. As a result the development of working methodologies for digital refitting of fragments is of fundamental importance for archaeological research and conservation practice. This study presents a comparative analysis of manual and digital reconstruction, which has never been explored even if computer scientists have achieved many developments in the field of digital refitting. Results indicate the parallels between manual and digital processes in terms of durability, integrity and practicality. Also, in order to provide methodological directions to conservators, three different semi-automatic fragments matching approaches based on their effectiveness in managing the project and alignment of fragments were ...

Journal of King Saud University - Computer and Information Sciences, 2018

The ancient pottery is often found in archaeological sites in a broken state, especially when those pieces of unknown organisms and irregular fragments, may take years of hard work, especially in the case of loss of some pieces or require hard work and experienced archaeologists. So this problem is divided into two major tasks the first of which is the Classification of Archaeological Fragments into similar groups (CAF) and the second one is the Reconstruction of each group into the original Archaeological Objects (RAO). To solve this problem, a method has been proposed, which exploits the color and texture properties of the surfaces of the fragments. Furthermore, the reconstruction of archaeological fragments in 3D geometry is an important problem in pattern recognition. Therefore, this research has implemented the algorithms to reconstruct real datasets using Neural Networks. The challenge of this work is to reconstruct the objects without previous knowledge about the part that should start the assembly; this greatly helps to avoid the presence of gaps created due to missing artifact fragments. The study utilizes the geometric features of the fragments as important features to reconstruct the objects by classifying their fragments using a Neural Network model.

There exist many archeological objects which are broken in pieces. It is always important to find the neighbouring pieces so that different parts of the object can be put together and the original object reconstructed. Direct evaluation of broken objects has several disadvantages, such as being difficult and time-consuming. As an alternative, indirect techniques like photogrammetry and laser scanning can be applied, in which measurements of object pieces can be made and the overall shape of the object constructed by inspection of the relation between models of object parts. When compared with direct techniques, such methods enjoy being fast and non-contact so leading to the increased safety of the objects under reconstruction. In this project, photogrammetry is used to extract edges of the broken parts. The mathematical relations between the edges are then examined, the neighbouring parts are found and the model of the object is formed. This paper studies various parameters each of which defines some mathematical relation between parts of an object. The experiments carried out show that the radius of curvature is a suitable parameter which can be used to find the neighbouring pieces of the modelled object. The results show enough accuracy for 3D modelling of the object with the specified dimensions in our experiments. But in order to verify the validity of this method, it should be applied to a wide range of archaeological objects.

ETRI Journal, 2020

The reconstruction of archaeological fragments in 3D geometry is an important problem in pattern recognition and computer vision. Therefore, we implement an algorithm with the help of a 3D model to perform reconstruction from the real datasets using the slope features. This approach avoids the problem of gaps created through the loss of parts of the artifacts. Therefore, the aim of this study is to assemble the object without previous knowledge about the form of the original object. We utilize the edges of the fragments as an important feature in reconstructing the objects and apply multiple procedures to extract the 3D edge points. In order to assign the positions of the unknown parts that are supposed to match, the contour must be divided into four parts. Furthermore, to classify the fragments under reconstruction, we apply a backpropagation neural network. We test the algorithm on several models of ceramic fragments. It achieves highly accurate results in reconstructing the objects into their original forms, in spite of absent pieces. K E Y W O R D S 3D geometry, archaeological fragments, ceramic, neural network, pottery | 421 RASHEED AnD nORDIn aims to propose a new method for aligning and matching two different edges of a pair of fragments and finding the corresponding point set, which is important to matching many types of fragments.