An Overview of Methods for Automatic Reassembly of Fragmented Objects

An Overview of Methods for Automatic Reassembly of Fragmented Objects

Dimitris Arabadjis (National Technical University of Athens, Greece), Michael Exarhos (National Technical University of Athens, Greece), Fotios Giannopoulos (National Technical University of Athens, Greece), Solomon Zannos (National Technical University of Athens, Greece), Panayiotis Rousopoulos (National Technical University of Athens, Greece) and Constantin Papaodysseus (National Technical University of Athens, Greece)
DOI: 10.4018/978-1-60960-786-9.ch008
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In this chapter the authors outline some research works characteristic for the application of Signal Processing and Pattern Analysis techniques to the automatic reconstruction / reassembly of fragmented archaeological objects. The studies described in the chapter cover in their application cases a variety of archaeological objects, ranging from documents and wall-paintings to pots and sculptures. Moreover there are distinct approaches in the treatment of these application cases, with some works focusing on the development of a reconstruction methodology of general purpose, while others aim to develop a complete system to treat a specific application problem. The methodologies developed in these studies are outlined in the chapter so as to retain the basic technical elements of each approach that compile the proposed reconstruction algorithmic scheme.
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1. Introduction

One of the most important parts in the disciplines of Archaeology and History is the extraction of information from excavated finds. These finds that come to light are of huge importance, as they reveal details not only about very important events in human history, but also for the everyday life in Ancient Times, the social structures of cities and civilizations that may not even exist anymore and their social activities. Unfortunately, due to the wear of time and other special conditions (natural disasters or human intervention), most of these finds are, as a rule, unearthed in pieces. For example, in the Greek island of Thera, frescos (wall-paintings) of great archaeological and historical importance have been excavated in thousands of pieces, preventing scholars of getting direct access to a great source of information. Similarly, in the celebrated archaeological sites of Mycenae and Tiryns thousands of wall-paintings’ fragments have been unearthed so far, starting from the excavations of Schliemann. Greece is clearly not the only country in which important archaeological finds are excavated fragmented; on the contrary, very important finds are excavated broken in various locations in Egypt, Italy, Syria, Jordan, Israel, etc.

As a result, a great effort is being undertaken by the scientific community for the reassembly of such fragmented finds. This procedure demands special trained staff, a considerable amount of money and consumes a lot of time. Hence, in the past years, a lot of attempts have been made for the development of various automated systems that could contribute to this effort. The role of these systems is to point out possible matches of fragments to scholars and the dedicated personnel, in order to assist them in the reconstruction of the finds. These systems must propose all possible matches, trying, in the same time, to give as less false positive matches as possible. In the present chapter, a number of publications on the subject are presented.

The basic algorithmic scheme of the reconstruction methods presented here consists of 3 basic sub-processes:

  • 1.

    Preprocessing Stage: In the preprocessing of fragments digital representations (photographs or 3D scanning representations) necessary information should be extracted that will be used as input in the subsequent fragments matching process. In this stage the methods usually evaluate the features selected to describe fragments characteristics used to trace possible matching between fragments.

  • 2.

    Matching Error Evaluation: Based on the features extracted in the preprocessing, in this stage matching error measures are usually developed so as to obtain matching estimations from fragments features variations.

  • 3.

    Matching Decision: After calculating matching estimates between fragments, in this stage the methods evaluate virtual reconstruction of matching fragments islands. Consistency of this reconstruction is depended on the strictness of the matching criteria and the way inconsistent pairwise matching decisions are lifted.

Complete Chapter List

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Table of Contents
Constantin Papaodysseus
Chapter 1
Ioulia Papageorgiou
Quantitative Archaeology had a rapid development in the past few decades due to the parallel development of methodologies in Physics, Chemistry and... Sample PDF
Applications of Computational and Model-Based Statistical Methodologies in Archaeology
Chapter 2
Alicia Fornés, Josep Lladós, Gemma Sánchez, Horst Bunke
Writer identification in handwritten text documents is an active area of study, whereas the identification of the writer of graphical documents is... Sample PDF
Writer Identification in Old Handwritten Music Scores
Chapter 3
Panayiotis Rousospoulos, Dimitris Arabadjis, Mihalis Exarhos, Michail Panagopoulos, Georgios Galanopoulos, Afroditi Pantazi, Constantin Papaodysseus
The present chapter deals with the problem of determining the method used to draw several celebrated and beautiful wall-paintings belonging to the... Sample PDF
A Digital Investigation Manifesting use of Geometric Stencils for the Drawing of Akrotiri Thera Prehistoric Wall Paintings
Chapter 4
P. Kapsalas, M. Zervakis, P. Maravelaki-Kalaitzaki, E.T. Delegou, A. Moropoulou
The systematic analysis of corrosion damage on cultural heritage objects is an aspect of multidisciplinary interest. The application of... Sample PDF
Machine Vision Schemes towards Detecting and Estimating The State Of Corrosion
Chapter 5
Epaminondas E. Panas
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Functional Form, Elasticity and Lexical Richness: Estimates and Implications
Chapter 6
Filippo Stanco, Davide Tanasi, Giuseppe Claudio Guarnera, Giovanni Gallo
An important feature of the Minoan culture is the pottery of Kamares style, that documents the Cretan cultural production between the first half of... Sample PDF
Automatic Classification of Decorative Patterns in the Minoan Pottery of Kamares Style
Chapter 7
Constantin Papaodysseus, Michail Panagopoulos, Panayotis Rousopoulos, Dimitris Arabadjis, Fivi Panopoulou, Solomon Zannos, Fotios Giannopoulos, Steven Tracy
Automatic handwriting identification/classification is a major problem in graphology analysis. In this chapter the authors present an automated... Sample PDF
Automatic Identification of the Writer of Ancient Greek Inscriptions, Employing Methods of Computer Engineering and Mathematics
Chapter 8
Dimitris Arabadjis, Michael Exarhos, Fotios Giannopoulos, Solomon Zannos, Panayiotis Rousopoulos, Constantin Papaodysseus
In this chapter the authors outline some research works characteristic for the application of Signal Processing and Pattern Analysis techniques to... Sample PDF
An Overview of Methods for Automatic Reassembly of Fragmented Objects
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