Development of an Algorithmic Procedure for the Detection of Conjugate Fragments

Filippas, Dionysios; Georgopoulo, A.

doi:10.5194/isprsannals-ii-5-w1-127-2013

Cited by 3 publications

(6 citation statements)

References 17 publications

(6 reference statements)

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“…The idea that spawned the Fragmatch algorithm is that the comparison between the broken surfaces should be accomplished by a quick method, hence it should be linear if possible. That is the main innovation in relation to all previous investigations [4].…”

Section: Fragmatch Algorithmmentioning

confidence: 77%

A Novel Algorithm for Detecting Conjugate Archaeological Fragments

Filippas

Georgopoulos

2014

International Journal of Heritage in the Digital Era

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Matching fragmented archaeological parts has always puzzled archaeologists. Very few attempts have been made so far for the automation of this procedure and thus assisting scholars to this effect. In this paper an innovative method for the detection of conjugate fragments is proposed, which is based mainly on their geometry. The Fragmatch algorithm developed for that purpose is presented, together with an extensive analysis of both of its parts; the global and the partial matching of surfaces. The method proposed is based on the comparison of vectors and surfaces, performed linearly, for simplicity and speed. It addresses mainly fragments of relatively big architectural pieces. A series of simulations have been performed in order to test the limits of the algorithm for the noise and the accuracy of scanning, for the number of scan points, as well as for the wear of the surfaces and the diversity of shapes. Problems that have been encountered during the application of these examples are interpreted and ways of dealing with them are being proposed. In addition a practical application is presented to test the algorithm in real conditions. Finally, the key points of this effort are being mentioned, followed by an analysis of the advantages and disadvantages of the proposed Fragmatch algorithm along with proposals for future work.

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Section: Fragmatch Algorithmmentioning

confidence: 77%

A Novel Algorithm for Detecting Conjugate Archaeological Fragments

Filippas

Georgopoulos

2014

International Journal of Heritage in the Digital Era

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“…Advancements in low-cost and high-volume acquisition devices and computer systems have provided new tools for archaeologists to face the problem of reconstruction and improve the efficiency of work [6][7][8]. In recent years, computer-aided reconstruction systems have been developed to assist archaeologists.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, computer-aided reconstruction systems have been developed to assist archaeologists. Visualization and computer vision techniques, such as image processing and pattern recognition, have been applied in the reassembling of archaeological finds to facilitate their analysis and understandings [5][6][7][8][9]. These applications were carried out in two-dimensional (2D) or three-dimensional (3D) space [6,7].…”

Section: Introductionmentioning

confidence: 99%

“…So, the classification is conducted based on the similarities between features describing the fragments [20][21][22]. For the second mode, the feature extraction for classification is an essential part of pattern recognition, where the feature vector is a list of descriptions that includes sufficient information to identify a pattern [8,23]. In the literature, a variety of features were used to classify and reconstruct fragments, and a review of these methods up to 2019 is proposed in Reference [24].…”

Section: Introductionmentioning

confidence: 99%

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A Semi-Automatic Reconstruction of Archaeological Pottery Fragments from 2D Images Using Wavelet Transformation

et al. 2021

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The problem of matching fragments of three-dimensional (3D) objects has gained increasing attention, and several approaches have been developed to solve this problem. To date, however, to the best knowledge of the authors, there is no computer-based method supporting archaeologists in this activity. For this purpose, in this paper, a semi-automatic approach is proposed for the reconstruction of archaeological pottery fragments based on two-dimensional (2D) images. Firstly, the method, considering the curves as features, involves the extraction of edge curves by applying the Canny filter algorithm to the fragments’ image. Next, the wavelet transformation method is used to fit the edge curves and obtain the approximation coefficients. Then, the correlation coefficients between fragments are computed and the matching of fragments is done by comparing their values. The proposed approach is tested on some real cases. The results of the experimentation show, if compared with the state-of-the-art, that the method seems to be efficient and accurate in the reconstruction of pottery from 2D images of their fragments.

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“…Papaioannou and Karabassi (2003) combined curve matching techniques with a surface matching algorithm to estimate the positioning and respective matching error for the joining of three-dimensional fragmented objects. And Filippas and Georgopoulos (2013) presented a Fragmatch Algorithm that accepted as input data point clouds, i.e. X, Y, and Z for each point of the broken surfaces and not of the whole fragment.…”

Section: Introductionmentioning

confidence: 99%

Reassembling 3D Thin Fragments of Unknown Geometry in Cultural Heritage

Zheng

Huang

et al. 2014

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Many fragile antiques had already been broken upon being discovered at archaeology sites. The fragments of these objects cannot be effectively interpreted and studied unless they are successfully reassembled. However, there still exists many problems in the reassembly procedure in existing methods, such as the numerical instabilities of curvature and torsion based methods, the limitation of geometric assumption, and the error accumulation of the pairwise matching approach, etc. Regarding these problems, this paper proposed an approach to match the fragments to each other for their original 3D reconstruction. Instead of the curvatures and torsions, the approach is based on establishing a local Cartesian coordinate at every point of the 3D contour curves. First of all, the 3D meshes of the fragments are acquired by a structure-light based method, with the corresponding 3D contour curves extracted from the outer boundaries. Then, the contour curves are matched and aligned to each other by estimating all the possible 3D rigid transformations of the curve pairs with our defined local Cartesian coordinates, and then the maximum likelihood rigid transformations are selected. Finally, a global refinement is introduced to adjust the alignment errors and improve the final reassembling accuracy. In addition, experiments with two groups of fragments suggest that this approach cannot only match and align fragments effectively, but also improve the accuracy significantly. Comparing with the original 3D model acquired before being broken, the final reassembling accuracy reaches 0.47 mm.

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Development of an Algorithmic Procedure for the Detection of Conjugate Fragments

Cited by 3 publications

References 17 publications

A Novel Algorithm for Detecting Conjugate Archaeological Fragments

A Novel Algorithm for Detecting Conjugate Archaeological Fragments

A Semi-Automatic Reconstruction of Archaeological Pottery Fragments from 2D Images Using Wavelet Transformation

Reassembling 3D Thin Fragments of Unknown Geometry in Cultural Heritage

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