Evidence map›Paper›PMID 34300638›Full record

ArticleSensors (Basel, Switzerland)2021

Segmentation of Change in Surface Geometry Analysis for Cultural Heritage Applications.

Sunita Saha, Jacek Martusewicz, Noëlle L W Streeton, Robert Sitnik

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sunita SahaInstitute of Micromechanics and Photonics, Faculty of Mechatronics, Warsaw University of Technology, ul. Św. Andrzeja Boboli 8, 02-525 Warsaw, Poland.ORCID 0000-0001-7259-8994
Jacek MartusewiczFaculty of Conservation and Restoration of Works of Art, Academy of Fine Arts in Warsaw, ul. Krakowskie Przedmieście 5, 00-068 Warszawa, Poland.
Noëlle L W StreetonDepartment of Archaeology, Conservation & History, University of Oslo, P.O. Box 1072 Blindern, 0316 Oslo, Norway.
Robert SitnikInstitute of Micromechanics and Photonics, Faculty of Mechatronics, Warsaw University of Technology, ul. Św. Andrzeja Boboli 8, 02-525 Warsaw, Poland.ORCID 0000-0002-8156-5462

Funding

H2020 Marie Skłodowska-Curie Actions 813789
6 · The paper itself

Abstract

This work proposes a change-based segmentation method for applications to cultural heritage (CH) imaging to perform monitoring and assess changes at each surface point. It can be used as a support or component of the 3D sensors to analyze surface geometry changes. In this research, we proposed a new method to identify surface changes employing segmentation based on 3D geometrical data acquired at different time intervals. The geometrical comparison was performed by calculating point-to-point Euclidean distances for each pair of surface points between the target and source geometry models. Four other methods for local distance measurement were proposed and tested. In the segmentation method, we analyze the local histograms of the distances between the measuring points of the source and target models. Then the parameters of these histograms are determined, and predefined classes are assigned to target surface points. The proposed methodology was evaluated by considering two different case studies of restoration issues on CH surfaces and monitoring them over time. The results were presented with a colormap visualization for each category of the detected change in the analysis. The proposed segmentation method will help in the field of conservation and restoration for the documentation and quantification of geometrical surface change information. This analysis can help in decision-making for the assessment of damage and potential prevention of further damage, and the interpretation of measurement results.

Indexed as

AlgorithmsImaging, Three-Dimensional3D datageometric changeimagingmonitoringrestorationsegmentationvisualization

Identifiers

PMID34300638
PMCPMC8309812

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.