@misc{LangendorfPaetsch, author = {Langendorf, Jens and Paetsch, Olaf}, title = {GRAZIL (Graphical ZIB Language).}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-4518}, number = {TR-87-07}, abstract = {GRAZIL ist ein interaktives Programmpaket zur graphischen Darstellung von zwei-dimensionalen Kurvenverl{\"a}ufen. Dem Benutzer stehen zahlreiche Kommandos zum Gestalten des Layouts der Zeichnung zur Verf{\"u}gung. Die Eingabedaten m{\"u}ssen dem ZUGRIFF- Konzept gen{\"u}gen, wodurch die genaue Struktur der Daten erst zur Laufzeit bekannt sein muß und somit eine hohe Flexibilit{\"a}t und eine große Bandbreite der Einsatzm{\"o}glichkeiten erreicht wird. GRAZIL wurde mit der graphischen Grundsoftware BIZEPS2 und GKS entwickelt. Dadurch kann ein breites Rechner- und Ausgabeger{\"a}tespektrum genutzt werden.}, language = {de} } @misc{BuhtzLangendorfPaetsch, author = {Buhtz, Danuta Anna and Langendorf, Jens and Paetsch, Olaf}, title = {GRAZIL - 3D. Ein graphisches Anwendungsprogramm zur Darstellung von Kurven- und Funktionsverl{\"a}ufen im r{\"a}umlichen Koordinatensystem.}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-4556}, number = {TR-88-04}, abstract = {GRAZIL - 3D ist ein interaktives Programmpaket zur graphischen Darstellung von dreidimensionalen Kurvenverl{\"a}ufen. Das Aussehen der r{\"a}umlichen Ausgabe des Bildes wird durch Angabe des Blickwinkels und der Perspektive festgelegt.}, language = {de} } @misc{BuhtzLangendorfPaetschetal., author = {Buhtz, Rainer and Langendorf, Jens and Paetsch, Olaf and Buhtz, Danuta Anna}, title = {ZUGRIFF - Eine vereinheitlichte Datenspezifikation f{\"u}r graphische Darstellungen und ihre graphische Aufbereitung.}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-4506}, number = {TR-87-06}, abstract = {ZUGRIFF ist eine Dateischnittstelle f{\"u}r Graphikausgabe speziell numerischer Anwenderprogramme. Dieser Report beschreibt den Leistungsumfang der Spezifikation sowie die interaktive graphische Verarbeitung von ZUGRIFF- Dateien.}, language = {de} } @misc{LangendorfPaetsch, author = {Langendorf, Jens and Paetsch, Olaf}, title = {GRAZIL - Beschreibung der Version 6.0 des Plotpaketes.}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-4930}, number = {TR-93-01}, abstract = {GRAZIL ist ein interaktives Programmpaket zur grafischen Darstellung von zwei-dimensionalen Kurvenverl{\"a}ufen. Dem Benutzer stehen zahlreiche Kommandos und ein grafisches User-Interface zum Gestalten des Layouts der Zeichnung zur Verf{\"u}gung. Die Eingabedaten m{\"u}ssen dem GRAZIL-Eingabe-Format gen{\"u}gen. Somit wird eine hohe Flexibilit{\"a}t und eine gro\"se Bandbreite der Einsatzm{\"o}glichkeiten erreicht. GRAZIL wurde mit der grafischen Grundsoftware GKS entwickelt. Dadurch kann ein breites Rechner- und Ausgabeger{\"a}tespektrum genutzt werden.}, language = {de} } @misc{KuehnKorzenPaetsch, author = {K{\"u}hn, Wolfgang and Korzen, Manfred and Paetsch, Olaf}, title = {Fast Data Assimilation in Fire Tests of Steel Members}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-3766}, number = {SC-98-33}, abstract = {This report presents a fast data assimilation method to produce an interpolating time and space temperature distribution for steel members subject to fire testing. The method assimilates collected temperature data into the numerical integration of the heat equation. This physically based method also allows the computation of lateral and axial heat flux into and inside the member.}, language = {en} } @misc{PaetschBaumEbelletal., author = {Paetsch, Olaf and Baum, Daniel and Ebell, Gino and Ehrig, Karsten and Heyn, Andreas and Meinel, Dietmar and Prohaska, Steffen}, title = {Korrosionsverfolgung in 3D-computertomographischen Aufnahmen von Stahlbetonproben}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-50912}, abstract = {Kurzfassung. Durch die Alkalit{\"a}t des Betons wird Betonstahl dauerhaft vor Korrosion gesch{\"u}tzt. Infolge von Chlorideintrag kann dieser Schutz nicht l{\"a}nger aufrechterhalten werden und f{\"u}hrt zu Lochkorrosion. Die zerst{\"o}rungsfreie Pr{\"u}fung von Stahlbetonproben mit 3D-CT bietet die M{\"o}glichkeit, eine Probe mehrfach gezielt vorzusch{\"a}digen und den Korrosionsfortschritt zu untersuchen. Zur Quantifizierung des Sch{\"a}digungsgrades m{\"u}ssen die bei dieser Untersuchung anfallenden großen Bilddaten mit Bildverarbeitungsmethoden ausgewertet werden. Ein wesentlicher Schritt dabei ist die Segmentierung der Bilddaten, bei der zwischen Korrosionsprodukt (Rost), Betonstahl (BSt), Beton, Rissen, Poren und Umgebung unterschieden werden muss. Diese Segmentierung bildet die Grundlage f{\"u}r statistische Untersuchungen des Sch{\"a}digungsfortschritts. Hierbei sind die {\"A}nderung der BSt-Geometrie, die Zunahme von Korrosionsprodukten und deren Ver{\"a}nderung {\"u}ber die Zeit sowie ihrer r{\"a}umlichen Verteilung in der Probe von Interesse. Aufgrund der Gr{\"o}ße der CT-Bilddaten ist eine manuelle Segmentierung nicht durchf{\"u}hrbar, so dass automatische Verfahren unabdingbar sind. Dabei ist insbesondere die Segmentierung der Korrosionsprodukte in den Bilddaten ein schwieriges Problem. Allein aufgrund der Grauwerte ist eine Zuordnung nahezu unm{\"o}glich, denn die Grauwerte von Beton und Korrosionsprodukt unterscheiden sich kaum. Eine formbasierte Suche ist nicht offensichtlich, da die Korrosionsprodukte in Beton diffuse Formen haben. Allerdings l{\"a}sst sich Vorwissen {\"u}ber die Ausbreitung der Korrosionsprodukte nutzen. Sie bilden sich in r{\"a}umlicher N{\"a}he des BSt (in Bereichen vorheriger Volumenabnahme des BSt), entlang von Rissen sowie in Porenr{\"a}umen, die direkt am BSt und in dessen Nahbereich liegen. Davon ausgehend wird vor der Korrosionsprodukterkennung zun{\"a}chst eine BSt-Volumen-, Riss- und Porenerkennung durchgef{\"u}hrt. Dieser in der Arbeit n{\"a}her beschriebene Schritt erlaubt es, halbautomatisch Startpunkte (Seed Points) f{\"u}r die Korrosionsprodukterkennung zu finden. Weiterhin werden verschiedene in der Bildverarbeitung bekannte Algorithmen auf ihre Eignung untersucht werden.}, language = {de} } @misc{PaetschStallingKorzen1997, author = {Paetsch, Olaf and Stalling, Detlev and Korzen, Manfred}, title = {Online-Visualisierung von Brandversuchen an Bauteilen}, publisher = {Konrad-Zuse-Zentrum f{\"u}r Informationstechnik, Berlin (ZIB) / Bundesanstalt f{\"u}r Materialfoschung und -pr{\"u}fung (BAM) Berlin}, year = {1997}, language = {en} } @inproceedings{KorzenSchrieverZieneretal.1996, author = {Korzen, Manfred and Schriever, Robert and Ziener, Kai-Uwe and Paetsch, Olaf and Zumbusch, Gerd}, title = {Real-Time 3-D Visualization of Surface Temperature Fields Measured by Thermocouples on Steel Strutures in Fire Engineering}, series = {Proc. Int. Symposium Local Strain and Temperature Measurements in Non-Uniform Fields at Elevated Temperatures}, booktitle = {Proc. Int. Symposium Local Strain and Temperature Measurements in Non-Uniform Fields at Elevated Temperatures}, editor = {Ziebs, J. al.}, publisher = {Woodhead}, address = {England}, pages = {253 -- 262}, year = {1996}, language = {en} } @inproceedings{PaetschBaumProhaskaetal., author = {Paetsch, Olaf and Baum, Daniel and Prohaska, Steffen and Ehrig, Karsten and Meinel, Dietmar and Ebell, Gino}, title = {3D Corrosion Detection in Time-dependent CT Images of Concrete}, series = {DIR-2015 Proceedings}, booktitle = {DIR-2015 Proceedings}, abstract = {In civil engineering, the corrosion of steel reinforcements in structural elements of concrete bares a risk of stability-reduction, mainly caused by the exposure to chlorides. 3D computed tomography (CT) reveals the inner structure of concrete and allows one to investigate the corrosion with non-destructive testing methods. To carry out such investigations, specimens with a large artificial crack and an embedded steel rebar have been manufactured. 3D CT images of those specimens were acquired in the original state. Subsequently three cycles of electrochemical pre-damaging together with CT imaging were applied. These time series have been evaluated by means of image processing algorithms to segment and quantify the corrosion products. Visualization of the results supports the understanding of how corrosion propagates into cracks and pores. Furthermore, pitting of structural elements can be seen without dismantling. In this work, several image processing and visualization techniques are presented that have turned out to be particularly effective for the visualization and segmentation of corrosion products. Their combination to a workflow for corrosion analysis is the main contribution of this work.}, language = {en} } @inproceedings{AgudoJacomeHegePaetschetal., author = {Agudo J{\´a}come, Leonardo and Hege, Hans-Christian and Paetsch, Olaf and P{\"o}thkow, Kai}, title = {3D Reconstruction, Visualization and Quantification of Dislocations from Transmission Electron Microscopy Stereo-Pairs}, series = {Microscopy and Microanalysis 2016, July 24-28 Columbus, Ohio}, booktitle = {Microscopy and Microanalysis 2016, July 24-28 Columbus, Ohio}, language = {en} } @article{PaetschBaumProhaskaetal., author = {Paetsch, Olaf and Baum, Daniel and Prohaska, Steffen and Ehrig, Karsten and Ebell, Gino and Meinel, Dietmar and Heyn, Andreas}, title = {Korrosionsverfolgung in 3D-computertomographischen Aufnahmen von Stahlbetonproben}, series = {DGZfP-Jahrestagung 2014 Konferenzband}, journal = {DGZfP-Jahrestagung 2014 Konferenzband}, language = {de} } @inproceedings{JacomeEggelerPoethkowetal., author = {J{\´a}come, Leonardo Agudo and Eggeler, Gunter and P{\"o}thkow, Kai and Paetsch, Olaf and Hege, Hans-Christian}, title = {Three-Dimensional Characterization of Superdislocation Interactions in the High Temperature and Low Stress Creep Regime of Ni-Base Superalloy Single Crystals}, series = {Proceedings of CREEP 2015 - 13th International Conference on Creep and Fracture of Engineering Materials and Structures, May 31 - June 4, 2015, Toulouse, France}, booktitle = {Proceedings of CREEP 2015 - 13th International Conference on Creep and Fracture of Engineering Materials and Structures, May 31 - June 4, 2015, Toulouse, France}, pages = {16 -- 17}, abstract = {Monocrystaline Ni-base superalloys are the material of choice for first row blades in jet engine gas turbines. Using a novel visualization tool for 3D reconstruction and visualization of dislocation line segments from stereo-pairs of scanning transmission electron microscopies, the superdislocation substructures in Ni-base superalloy LEK 94 (crept to ε = 26\%) are characterized. Probable scenarios are discussed, how these dislocation substructures form.}, language = {en} } @inproceedings{StreicherPaetschSeileretal., author = {Streicher, Doreen and Paetsch, Olaf and Seiler, Robert and Prohaska, Steffen and Krause, Martin and Boller, Christian}, title = {3-D-Visualisierung von Radar- und Ultraschallecho-Daten mit ZIBAmira}, series = {Proc. DGZfP-Jahrestagung 2011}, booktitle = {Proc. DGZfP-Jahrestagung 2011}, language = {de} } @inproceedings{EhrigGoebbelsMeineletal.2011, author = {Ehrig, Karsten and Goebbels, J{\"u}rgen and Meinel, Dietmar and Paetsch, Olaf and Prohaska, Steffen and Zobel, Valentin}, title = {Comparison of Crack Detection Methods for Analyzing Damage Processes in Concrete with Computed Tomography}, series = {International Symposium on Digital Industrial Radiology and Computed Tomography}, booktitle = {International Symposium on Digital Industrial Radiology and Computed Tomography}, year = {2011}, language = {en} } @inproceedings{PaetschBaumEhrigetal.2012, author = {Paetsch, Olaf and Baum, Daniel and Ehrig, Karsten and Meinel, Dietmar and Prohaska, Steffen}, title = {Vergleich automatischer 3D-Risserkennungsmethoden f{\"u}r die quantitative Analyse der Schadensentwicklung in Betonproben mit Computer-Tomographie}, series = {Tagungsband der DACH Jahrestagung 2012}, booktitle = {Tagungsband der DACH Jahrestagung 2012}, year = {2012}, language = {de} } @inproceedings{PaetschBaumBressleretal.2013, author = {Paetsch, Olaf and Baum, Daniel and Breßler, David and Ehrig, Karsten and Meinel, Dietmar and Prohaska, Steffen}, title = {3-D-Visualisierung und statistische Analyse von Rissen in mit Computer-Tomographie untersuchten Betonproben}, series = {Tagungsband der DGZfP Jahrestagung 2013}, booktitle = {Tagungsband der DGZfP Jahrestagung 2013}, year = {2013}, language = {de} } @inproceedings{PaetschBaumEhrigetal.2012, author = {Paetsch, Olaf and Baum, Daniel and Ehrig, Karsten and Meinel, Dietmar and Prohaska, Steffen}, title = {Automated 3D Crack Detection for Analyzing Damage Processes in Concrete with Computed Tomography}, series = {Proceedings of Conference on Industrial Computed Tomography}, booktitle = {Proceedings of Conference on Industrial Computed Tomography}, pages = {321 -- 330}, year = {2012}, language = {en} } @inproceedings{MeinelEhrigLhostisetal.2014, author = {Meinel, Dietmar and Ehrig, Karsten and Lhostis, Valrie and Muzeau, Benoist and Paetsch, Olaf}, title = {Examination of Damage Processes in Concrete with CT}, series = {Proceedings of Conference on Industrial Computed Tomography}, booktitle = {Proceedings of Conference on Industrial Computed Tomography}, year = {2014}, language = {en} } @inproceedings{Paetsch, author = {Paetsch, Olaf}, title = {Possibilities and Limitations of Automatic Feature Extraction shown by the Example of Crack Detection in 3D-CT Images of Concrete Specimen}, series = {iCT 2019}, booktitle = {iCT 2019}, abstract = {To assess the influence of the alkali-silica reaction (ASR) on pavement concrete 3D-CT imaging has been applied to concrete samples. Prior to imaging these samples have been drilled out of a concrete beam pre-damaged by fatigue loading. The resulting high resolution 3D-CT images consist of several gigabytes of voxels. Current desktop computers can visualize such big datasets without problems but a visual inspection or manual segmentation of features such as cracks by experts can only be carried out on a few slices. A quantitative analysis of cracks requires a segmentation of the whole specimen which could only be done by an automatic feature detection. This arises the question of the reliability of an automatic crack detection algorithm, its certainty and limitations. Does the algorithm find all cracks? Does it find too many cracks? Can parameters of that algorithm, once identified as good, be applied to other samples as well? Can ensemble computing with many crack parameters overcome the difficulties with parameter finding? By means of a crack detection algorithm based on shape recognition (template matching) these questions will be discussed. Since the author has no access to reliable ground truth data of cracks the assessment of the certainty of the automatic crack is restricted to visual inspection by experts. Therefore, an artificial dataset based on a combination of manually segmented cracks processed together with simple image processing algorithms is used to quantify the accuracy of the crack detection algorithm. Part of the evaluation of cracks in concrete samples is the knowledge of the surrounding material. The surrounding material can be used to assess the detected cracks, e.g. micro-cracks within the aggregate-matrix interface may be starting points for cracks on a macro scale. Furthermore, the knowledge of the surrounding material can help to find better parameter sets for the crack detection itself because crack characteristics may vary depending on their surrounding material. Therefore, in addition to a crack detection a complete segmentation of the sample into the components of concrete, such as aggregates, cement matrix and pores is needed. Since such a segmentation task cannot be done manually due to the amount of data, an approach utilizing convolutional neuronal networks stemming from a medical application has been applied. The learning phase requires a ground truth i.e. a segmentation of the components. This has to be created manually in a time-consuming task. However, this segmentation can be used for a quantitative evaluation of the automatic segmentation afterwards. Even though that work has been performed as a short term subtask of a bigger project funded by the German Research Foundation (DFG) this paper discusses problems which may arise in similar projects, too.}, language = {en} } @article{AgudoJacomeHegePaetschetal., author = {Agudo J{\´a}come, Leonardo and Hege, Hans-Christian and Paetsch, Olaf and P{\"o}thkow, Kai}, title = {Three-dimensional reconstruction and quantification of dislocation substructures from transmission electron microscopy stereo pairs}, series = {Ultramicroscopy}, volume = {195}, journal = {Ultramicroscopy}, doi = {10.1016/j.ultramic.2018.08.015}, pages = {157 -- 170}, abstract = {A great amount of material properties is strongly influenced by dislocations, the carriers of plastic deformation. It is therefore paramount to have appropriate tools to quantify dislocation substructures with regard to their features, e.g., dislocation density, Burgers vectors or line direction. While the transmission electron microscope (TEM) has been the most widely-used equipment implemented to investigate dislocations, it usually is limited to the two-dimensional (2D) observation of three-dimensional (3D) structures. We reconstruct, visualize and quantify 3D dislocation substructure models from only two TEM images (stereo pairs) and assess the results. The reconstruction is based on the manual interactive tracing of filiform objects on both images of the stereo pair. The reconstruction and quantification method are demonstrated on dark field (DF) scanning (S)TEM micrographs of dislocation substructures imaged under diffraction contrast conditions. For this purpose, thick regions (>300 nm) of TEM foils are analyzed, which are extracted from a Ni-base superalloy single crystal after high temperature creep deformation. It is shown how the method allows 3D quantification from stereo pairs in a wide range of tilt conditions, achieving line length and orientation uncertainties of 3\% and 7°, respectively. Parameters that affect the quality of such reconstructions are discussed.}, language = {en} } @inproceedings{Paetsch, author = {Paetsch, Olaf}, title = {M{\"o}glichkeiten und Grenzen automatischer Merkmalserkennung am Beispiel von Risserkennungen in 3D-CT-Aufnahmen von Betonproben}, publisher = {iCT 2019}, address = {https://www.ndt.net/article/ctc2019/papers/iCT2019_Full_paper_29.pdf}, abstract = {Die Auswertungen der großen Datenmengen moderner bildgebender Verfahren der ZfP k{\"o}nnen manuell kaum noch bew{\"a}ltigt werden. Hochaufl{\"o}sende 3D-CT-Aufnahmen bestehen oft aus {\"u}ber 1000 Schichtbildern mit einer Datenmenge von mehreren Gigabytes. Aktuelle Computer k{\"o}nnen diese zwar problemlos visualisieren und erlauben somit eine visuelle Inspektion, aber die m{\"o}glichst vollst{\"a}ndige Erkennung bestimmter Merkmale in den Daten und deren qualitative wie quantitative Auswertung ist durch Experten manuell nicht mehr zu bew{\"a}ltigen. Das gilt insbesondere im Kontext der Schadensaufkl{\"a}rung f{\"u}r die quantitative Analyse verschiedenartig induzierter Risse in Betonen (z.B. durch mechanische Belastungen sowie Frost, Sulfat und Alkali-Kiesels{\"a}ure-Reaktion). Eine dazu notwendige Segmentierung und Merkmalserkennung kann nur automatisch durchgef{\"u}hrt werden. Dabei ergibt sich (auch fast automatisch) die Frage nach der Verl{\"a}sslichkeit der verwendeten Algorithmen. Inwieweit kann man davon ausgehen, dass alle gesuchten Merkmale auch tats{\"a}chlich gefunden worden sind? Sind die gefundenen Merkmale quantitativ auswertbar und wie wirken sich Parameter{\"a}nderungen auf die Ergebnisse aus? Sollten immer dieselben, einmal mit gutem Ergebnis angewandten, Parameter auch bei anderen Proben zur besseren Vergleichbarkeit genutzt werden? Anhand eines Risserkennungsalgorithmus basierend auf Formerkennung und Bildverarbeitung wird die Problematik diskutiert. Als Grundlage zur Bewertung des Ansatzes dienen 3D-CT-Aufnahmen von gesch{\"a}digten Betonprobek{\"o}rpern und Datens{\"a}tze, in denen sich aufgrund ihres homogenen Aufbaus mit einfachen Mitteln Risse sicher und eindeutig erkennen lassen. Zur Auswertung der erkannten Risse geh{\"o}rt auch deren Einbettung in das umliegende Material. Das erfordert neben einer automatischen Risserkennung auch eine Segmentierung des gesamten Probek{\"o}rpers in Zementsteinmatrix, Gesteinsk{\"o}rnung und Porenraum. Da eine solche Segmentierung aufgrund der Datenmenge nur schwer manuell erfolgen kann, werden erste Ergebnisse aus einer Segmentierung mit Hilfe selbstlernender Convolutional Neural Networks gezeigt.}, language = {de} } @misc{AgudoJacomeHegePaetschetal., author = {Agudo J{\´a}come, Leonardo and Hege, Hans-Christian and Paetsch, Olaf and P{\"o}thkow, Kai}, title = {Three-Dimensional Reconstruction and Quantification of Dislocation Substructures from Transmission Electron Microscopy Stereo-Pairs}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-70339}, abstract = {A great amount of material properties is strongly influenced by dislocations, the carriers of plastic deformation. It is therefore paramount to have appropriate tools to quantify dislocation substructures with regard to their features, e.g., dislocation density, Burgers vectors or line direction. While the transmission electron microscope (TEM) has been the most widely-used equipment implemented to investigate dislocations, it usually is limited to the two-dimensional (2D) observation of three-dimensional (3D) structures. We reconstruct, visualize and quantify 3D dislocation substructure models from only two TEM images (stereo-pairs) and assess the results. The reconstruction is based on the manual interactive tracing of filiform objects on both images of the stereo-pair. The reconstruction and quantification method are demonstrated on dark field (DF) scanning (S)TEM micrographs of dislocation substructures imaged under diffraction contrast conditions. For this purpose, thick regions (> 300 nm) of TEM foils are analyzed, which are extracted from a Ni-base superalloy single crystal after high temperature creep deformation. It is shown how the method allows 3D quantification from stereo-pairs in a wide range of tilt conditions, achieving line length and orientation uncertainties of 3 \% and 7°, respectively. Parameters that affect the quality of such reconstructions are discussed.}, language = {en} } @inproceedings{Paetsch, author = {Paetsch, Olaf}, title = {Possibilities and Limitations of Automatic Feature Extraction shown by the Example of Crack Detection in 3D-CT Images of Concrete Specimen}, series = {iCT 2019}, booktitle = {iCT 2019}, abstract = {To assess the influence of the alkali-silica reaction (ASR) on pavement concrete 3D-CT imaging has been applied to concrete samples. Prior to imaging these samples have been drilled out of a concrete beam pre-damaged by fatigue loading. The resulting high resolution 3D-CT images consist of several gigabytes of voxels. Current desktop computers can visualize such big datasets without problems but a visual inspection or manual segmentation of features such as cracks by experts can only be carried out on a few slices. A quantitative analysis of cracks requires a segmentation of the whole specimen which could only be done by an automatic feature detection. This arises the question of the reliability of an automatic crack detection algorithm, its certainty and limitations. Does the algorithm find all cracks? Does it find too many cracks? Can parameters of that algorithm, once identified as good, be applied to other samples as well? Can ensemble computing with many crack parameters overcome the difficulties with parameter finding? By means of a crack detection algorithm based on shape recognition (template matching) these questions will be discussed. Since the author has no access to reliable ground truth data of cracks the assessment of the certainty of the automatic crack is restricted to visual inspection by experts. Therefore, an artificial dataset based on a combination of manually segmented cracks processed together with simple image processing algorithms is used to quantify the accuracy of the crack detection algorithm. Part of the evaluation of cracks in concrete samples is the knowledge of the surrounding material. The surrounding material can be used to assess the detected cracks, e.g. micro-cracks within the aggregate-matrix interface may be starting points for cracks on a macro scale. Furthermore, the knowledge of the surrounding material can help to find better parameter sets for the crack detection itself because crack characteristics may vary depending on their surrounding material. Therefore, in addition to a crack detection a complete segmentation of the sample into the components of concrete, such as aggregates, cement matrix and pores is needed. Since such a segmentation task cannot be done manually due to the amount of data, an approach utilizing convolutional neuronal networks stemming from a medical application has been applied. The learning phase requires a ground truth i.e. a segmentation of the components. This has to be created manually in a time-consuming task. However, this segmentation can be used for a quantitative evaluation of the automatic segmentation afterwards. Even though that work has been performed as a short term subtask of a bigger project funded by the German Research Foundation (DFG) this paper discusses problems which may arise in similar projects, too. [1.2MB | id=23664 ] iCT 2019 Session: Short talks Thu 13:50 Auditorium 2019-03 M{\"o}glichkeiten und Grenzen automatischer Merkmalserkennung am Beispiel von Risserkennungen in 3D-CT-Aufnahmen von Betonproben O. Paetsch11 Visualisation and Data Analysis; Konrad-Zuse-Institut Berlin (ZIB)18, Berlin, Germany Abstract [1MB | id=23104 ] DE DGZfP 2018 Session: Bauwesen 2018-09 Quantitative Rissanalyse im Fahrbahndeckenbeton mit der 3D-Computertomographie D. Meinel125, K. Ehrig128, F. Weise16, O. Paetsch211 1Division 8.5; BAM Federal Institute for Materials Research and Testing1277, Berlin, Germany 2Visualisation and Data Analysis; Konrad-Zuse-Institut Berlin (ZIB)18, Berlin, Germany concrete, ROI tomography, in-situ-CT, 3D-CT, Beton, AKR, Feuchtetransport, automatic crack detection Abstract [0.7MB | id=18980 ] DE DGZfP 2015 Session: CT Algorithmen 2016-04 3D Corrosion Detection in Time-dependent CT Images of Concrete O. Paetsch111, D. Baum15, S. Prohaska17, K. Ehrig228, D. Meinel225, G. Ebell24 1Visualisation and Data Analysis; Konrad-Zuse-Institut Berlin (ZIB)18, Berlin, Germany 2Division 8.5; BAM Federal Institute for Materials Research and Testing1277, Berlin, Germany CT, multi-angle radiography, defect detection, Feature Extraction, image processing, concrete, corrosion Abstract [0.5MB | id=18043 ] DIR 2015 Session: Quantitative imaging and image processing 2015-08 Korrosionsverfolgung in 3D-computertomographischen Aufnahmen von Stahlbetonproben O. Paetsch111, D. Baum15, G. Ebell24, K. Ehrig228, A. Heyn2, D. Meinel225, S. Prohaska17 1Konrad-Zuse-Institut Berlin (ZIB)18, Berlin, Germany 2Division VIII.3; BAM Federal Institute for Materials Research and Testing1277, Berlin, Germany Computertomographie [0.4MB | id=17375 ] DE DGZfP 2014 Session: Bauwesen 2015-03 Examination of Damage Processes in Concrete with CT D. Meinel125, K. Ehrig128, V. L'Hostis2, B. Muzeau2, O. Paetsch311 1BAM Federal Institute for Materials Research and Testing1277, Berlin, Germany 2Laboratoire d'Etude du Comportement des B{\´e}tons et des Argiles; Commissariat Energie Atomique (CEA)287, Gif-Sur-Yvette, France 3Konrad-Zuse-Institut Berlin (ZIB)18, Berlin, Germany X-ray computed tomography, concrete, corrosion, crack detection, 3D visualization Abstract [4.9MB | id=15692 ] iCT 2014 Session: Non-destructive Testing and 3D Materials Characterisation of... 2014-06 3-D-Visualisierung und statistische Analyse von Rissen in mit Computer-Tomographie untersuchten Betonproben O. Paetsch111, D. Baum15, D. Breßler1, K. Ehrig228, D. Meinel225, S. Prohaska1,17 1Konrad-Zuse-Institut Berlin (ZIB)18, Berlin, Germany 2Division VIII.3; BAM Federal Institute for Materials Research and Testing1277, Berlin, Germany Radiographic Testing (RT), statistical analysis, 3D Computed Tomography, visualization, concrete structural damage, automated crack detection [1MB | id=15343 ] DE DGZfP 2013 Session: Computertomographie 2014-03 Vergleich automatischer 3D-Risserkennungsmethoden f{\"u}r die quantitative Analyse der Schadensentwicklung in Betonproben mit Computertomographie O. Paetsch111, K. Ehrig228, D. Meinel225, D. Baum15, S. Prohaska1,1,17 1Konrad-Zuse-Institut Berlin (ZIB)18, Berlin, Germany 2Division VIII.3; BAM Federal Institute for Materials Research and Testing1277, Berlin, Germany Radiographic Testing (RT), visualization, crack detection, Visualisierung, computer tomography, template matching, Hessian eigenvalues, ZIBAmira, automated crack detection, percolation [0.9MB | id=14269 ] DE DGZfP 2012 Session: Computertomographie 2013-05 Automated 3D Crack Detection for Analyzing Damage Processes in Concrete with Computed Tomography O. Paetsch111, D. Baum15, K. Ehrig228, D. Meinel225, S. Prohaska1,1,17 1Konrad-Zuse-Institut Berlin (ZIB)18, Berlin, Germany 2Division VIII.3; BAM Federal Institute for Materials Research and Testing1277, Berlin, Germany computed tomography, template matching, Hessian eigenvalues, crack statistics, visualization, crack surface, ZIBAmira [0.6MB | id=13736 ] iCT 2012 Session: Poster - Analysis and Algorithms 2012-12 3-D-Visualisierung von Radar- und Ultraschallecho-Daten mit ZIBAmira D. Streicher112, O. Paetsch211, R. Seiler2, S. Prohaska27, M. Krause360 [Profile of Krause] , C. Boller178 1Saarland University74, Saarbr{\"u}cken, Germany 2Konrad-Zuse-Institut Berlin (ZIB)18, Berlin, Germany 3BAM Federal Institute for Materials Research and Testing1277, Berlin, Germany [0.4MB | id=12284 ] DE DGZfP 2011 Session: Bauwesen 2012-05 Comparison of Crack Detection Methods for Analyzing Damage Processes in Concrete with Computed Tomography K. Ehrig128, J. Goebbels153, D. Meinel125, O. Paetsch211, S. Prohaska27, V. Zobel2 1Division VIII.3; BAM Federal Institute for Materials Research and Testing1277, Berlin, Germany 2Konrad-Zuse-Institut Berlin (ZIB)18, Berlin, Germany [0.7MB | id=11150 ] DIR 2011 Session: Poster 2011-11 Actual Cooperations 10th International Workshop NDT in Progress 2019 2019 Oct 7-9 11th International Symposium on NDT in Aerospace 2019 2019 Nov 13-15 3rd Singapore International NDT Conference \& Exhibition, SINCE 2019 2019 Dec 4-5 10th Conference on Industrial Computed Tomography (iCT) 2020 2020 Feb 4-7 34th European Conference on Acoustic Emission Testing (EWGAE 2020) 2020 Sep 9-11 Contribute Papers and Proceedings to NDT.net Share... Home Exhibition Archive Forum Jobs Members Events Directory NDT A-Z Advertise Privacy Policy Contact About © NDT.net - Where expertise comes together. The Largest Open Access Portal of Nondestructive Testing (NDT)- since 1996}, language = {en} } @misc{KedziorskiKehlPaetsch, author = {Kedziorski, Rafal and Kehl, Detlef and Paetsch, Olaf}, title = {Client-Server-Anwendung zur Steuerung von Ausgabeger{\"a}ten}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-5658}, number = {TR-98-04}, abstract = {\\{\bf Zusammenfassung: }\noindent Die Steuerung von grafischen Ausgabeger{\"a}ten erfordert oft mehr als ein oder zwei Optionen, wie man sie vom UNIX {\em lpr}-Kommando kennt. Hier bietet sich eine grafische Benutzungsschnittstelle zur {\"u}bersichtlichen Einstellung aller m{\"o}glichen Parameter und Optionen an. Wenn dieses Ger{\"a}t zudem nur {\"u}ber eine besondere Treiber-Software zu bedienen ist und in einem heterogenen Intranet zur Verf{\"u}gung gestellt werden soll, ist eine Steuerung mittels eines WWW-Servers naheliegend. Im Folgenden sollen L{\"o}sungsans{\"a}tze diskutiert werden, die auf HTML/CGI- bzw. Java-Basis derartige Steuerung realisieren. {\small} It is often the case that graphical output devices need more than one or two control options like the UNIX {\em lpr}-command. A driver programme with a graphical user interface (GUI) can satisfy this requirement. If such a device shall be accessible in an heterogenous network a solution using a WWW-server can be used. Possible HTML/CGI resp. Java-based solutions are discussed in the following.}, language = {de} } @article{JungNowackaBarisinetal., author = {Jung, Christian and Nowacka, Anna and Barisin, Tin and Meinel, Dietmar and Paetsch, Olaf and Grzesiak, Szymon and Salamon, Michael and Schladitz, Katja and Redenbach, Claudia and Pahn, Matthias}, title = {3d imaging and analysis of cracks in loaded concrete samples. 12th Conference on Industrial Computed Tomography (iCT) 2023, 27 February - 2 March 2023 in F{\"u}rth, Germany}, series = {e-Journal of Nondestructive Testing}, volume = {28}, journal = {e-Journal of Nondestructive Testing}, number = {3}, doi = {10.58286/27721}, abstract = {Concrete plays a central role as the standard building material in civil engineering. Experimental characterization of the concrete microstructure and a description of failure mechanisms are important to understand the concrete's mechanical properties. Computed tomography is a powerful source of information as it yields 3d images of concrete specimens. However, complete visual inspection is often infeasible due to very large image sizes. Hence, automatic methods for crack detection and segmentation are needed. A region-growing algorithm and a 3d U-Net showed promising results in a previous study. Cracks in normal concrete and high-performance concrete that were initiated via tensile tests were investigated. Here, the methods are validated on a more diverse set of concrete types and crack characteristics. Adequate adaptions of the methods are necessary to deal with the complex crack structures. The segmentation results are assessed qualitatively and compared to those of a template matching algorithm which is well-established in industry.}, language = {en} }