Automated surface inspection of small customer-specific optical elements
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Alexander Schöch
Dr. Alexander Schöch received his BSc in computer engineering and his MSc in industrial engineering from the NTB where he worked on cryptoanalysis with FPGAs and highly parallelized software frameworks respectively. He received his PhD degree from the University of Padua for his work on the topic of metrology at elevated temperature and industrial process control. Currently, he is employed as a research associate at the Institute for Production Metrology, Materials and Technical Optics (PWO) of NTB. His interests include computer graphics, computer vision and machine learning technology.
Machine Vision Group, Institute for Production Metrology, Materials and Optics, NTB Interstate University of Applied Sciences of Technology Buchs, Werdenbergstrasse 4, 9471 Buchs, Switzerland
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Patric Perez
Patric Perez received a BSc in systems engineering with specialisation in computer engineering from the NTB. He created an interactive android teaching game for electrostatics and magnetism on bachelor level. Since his graduation he is employed at the Institute for Production Metrology, Materials and Technical Optics (PWO) of NTB as research associate. His main activities are planning and realisation of machine vision setups and subsequent image processing as applied research.
Machine Vision Group, Institute for Production Metrology, Materials and Optics, NTB Interstate University of Applied Sciences of Technology Buchs, Werdenbergstrasse 4, 9471 Buchs, Switzerland
Sabine Linz-Dittrich completed an apprenticeship as an optician at the company Zeiss in Jena. Afterwards she studied Optical Hardware and Spectroscopy Engineering at the institute LITMO in St. Petersburg, Russia. She completed her physics diploma thesis at the TU Berlin with the focus on thin film solar cells. During eleven years she was employed at Balzers Optics in Liechtenstein, there she gained experience as a development engineer in optical coatings as well as leading a production line of optical components. Since 2010 she is employed as a research associate at the Institute for Production Metrology, Materials and Technical Optics (PWO) of NTB.
Technical Optics Group, Institute for Production Metrology, Materials and Optics, NTB Interstate University of Applied Sciences of Technology Buchs, Werdenbergstrasse 4, 9471 Buchs, Switzerland
Prof. Dr. Carlo Bach received his diploma and his PhD in computer science from ETH Zurich. After several years in industry working in the field of artificial intelligence he joined the university of applied sciences NTB where he teaches computer science and image processing courses. Mr. Bach leads the machine vision group of the Institute for Production Metrology, Materials and Technical Optics (PWO). He is interested in all kinds of surface inspection with 2D and 3D methods.
Machine Vision Group, Institute for Production Metrology, Materials and Optics, NTB Interstate University of Applied Sciences of Technology Buchs, Werdenbergstrasse 4, 9471 Buchs, Switzerland
Carsten Ziolek finished his studies in physics at the University of Hanover in 1997 with a work on wavelength selection and Q-switching of erbium lasers. During his doctorate at the Laser Centre Hanover he worked on the laser dynamics of these systems. He earned his PhD in 2000 with a work on particular Erbium-based infrared-lasers for ophthalmology applications. From 2001 until 2015 he worked for the company TRUMPF in different positions, finally for more than 10 years as Head R&D of TRUMPF's marking lasers. In 2015 he was appointed as professor at the NTB. There he leads the Institute for Production Metrology, Materials and Optics as well as its technical optics and photonics field of competence. Carsten Ziolek is author of multiple technical publications and talks and is also involved in numerous patents.
Technical Optics Group, Institute for Production Metrology, Materials and Optics, NTB Interstate University of Applied Sciences of Technology Buchs, Werdenbergstrasse 4, 9471 Buchs, Switzerland
Abstract
In industry, manual visual inspection is typically applied to assess surface imperfections on basic optical elements according to the standard DIN ISO 14997. This article proposes a machine vision setup to mimic the human tester's inspection process. It consists of multiple cameras and LED light sources. Both are arranged on the surface of a hemisphere with the optical element to be inspected at its center. By enabling individual LED sources on the hemisphere, any movement during acquisition can be omitted. Thus, the system is capable of acquiring a sparse pseudo BRDF (Bidirectional Reflectance Distribution Function) representation of imperfections. It is shown by experiments that this representation allows to discriminate between certain imperfections. Besides the mechanical setup, the image processing methodology and classification results are discussed. A comparison to results from manual inspection for 20 optical elements of the same geometry is also presented. Results indicate that a good agreement with the de-facto standard manual inspection method from industry can be obtained by the system.
Zusammenfassung
Oberflächenunvollkommenheiten an optischen Grundelementen werden typischerweise durch manuelle Sichtprüfung nach der Norm DIN ISO 14997 beurteilt. In diesem Artikel wird ein bildverarbeitendes System beschrieben, um den Inspektionsprozess eines menschlichen Testers nachzuahmen und zu automatisieren. Es besteht aus mehreren Kameras und LED-Lichtquellen, welche auf der Oberfläche einer Halbkugel angeordnet sind. Das zu untersuchende optische Element ist in der Mitte der Halbkugel platziert. Durch die Aktivierung einzelner LED-Quellen auf der Halbkugel kann jede Bewegung bei der Erfassung weggelassen werden. Somit ist das System in der Lage, eine dünnbesetzte pseudo-BRDF Repräsentation von Unvollkommenheiten in weniger als einer Sekunde zu erhalten. Neben dem mechanischen Aufbau werden die eingesetzten Bildverarbeitungsmethoden diskutiert. Es wird durch Experimente gezeigt, dass diese Darstellung erlaubt, zwischen bestimmten Arten von Unvollkommenheiten zu unterscheiden. Neben dem mechanischen Aufbau wird die Bildverarbeitung und Klassifikation von Defekten beschrieben. Ein Vergleich zu Resultaten der manuellen Inspektion für 20 optische Elemente derselben Geometrie zeigt gute Übereinstimmung mit der de-facto Standard-Inspektionsmethode aus der Industrie.
About the authors
Dr. Alexander Schöch received his BSc in computer engineering and his MSc in industrial engineering from the NTB where he worked on cryptoanalysis with FPGAs and highly parallelized software frameworks respectively. He received his PhD degree from the University of Padua for his work on the topic of metrology at elevated temperature and industrial process control. Currently, he is employed as a research associate at the Institute for Production Metrology, Materials and Technical Optics (PWO) of NTB. His interests include computer graphics, computer vision and machine learning technology.
Machine Vision Group, Institute for Production Metrology, Materials and Optics, NTB Interstate University of Applied Sciences of Technology Buchs, Werdenbergstrasse 4, 9471 Buchs, Switzerland
Patric Perez received a BSc in systems engineering with specialisation in computer engineering from the NTB. He created an interactive android teaching game for electrostatics and magnetism on bachelor level. Since his graduation he is employed at the Institute for Production Metrology, Materials and Technical Optics (PWO) of NTB as research associate. His main activities are planning and realisation of machine vision setups and subsequent image processing as applied research.
Machine Vision Group, Institute for Production Metrology, Materials and Optics, NTB Interstate University of Applied Sciences of Technology Buchs, Werdenbergstrasse 4, 9471 Buchs, Switzerland
Sabine Linz-Dittrich completed an apprenticeship as an optician at the company Zeiss in Jena. Afterwards she studied Optical Hardware and Spectroscopy Engineering at the institute LITMO in St. Petersburg, Russia. She completed her physics diploma thesis at the TU Berlin with the focus on thin film solar cells. During eleven years she was employed at Balzers Optics in Liechtenstein, there she gained experience as a development engineer in optical coatings as well as leading a production line of optical components. Since 2010 she is employed as a research associate at the Institute for Production Metrology, Materials and Technical Optics (PWO) of NTB.
Technical Optics Group, Institute for Production Metrology, Materials and Optics, NTB Interstate University of Applied Sciences of Technology Buchs, Werdenbergstrasse 4, 9471 Buchs, Switzerland
Prof. Dr. Carlo Bach received his diploma and his PhD in computer science from ETH Zurich. After several years in industry working in the field of artificial intelligence he joined the university of applied sciences NTB where he teaches computer science and image processing courses. Mr. Bach leads the machine vision group of the Institute for Production Metrology, Materials and Technical Optics (PWO). He is interested in all kinds of surface inspection with 2D and 3D methods.
Machine Vision Group, Institute for Production Metrology, Materials and Optics, NTB Interstate University of Applied Sciences of Technology Buchs, Werdenbergstrasse 4, 9471 Buchs, Switzerland
Carsten Ziolek finished his studies in physics at the University of Hanover in 1997 with a work on wavelength selection and Q-switching of erbium lasers. During his doctorate at the Laser Centre Hanover he worked on the laser dynamics of these systems. He earned his PhD in 2000 with a work on particular Erbium-based infrared-lasers for ophthalmology applications. From 2001 until 2015 he worked for the company TRUMPF in different positions, finally for more than 10 years as Head R&D of TRUMPF's marking lasers. In 2015 he was appointed as professor at the NTB. There he leads the Institute for Production Metrology, Materials and Optics as well as its technical optics and photonics field of competence. Carsten Ziolek is author of multiple technical publications and talks and is also involved in numerous patents.
Technical Optics Group, Institute for Production Metrology, Materials and Optics, NTB Interstate University of Applied Sciences of Technology Buchs, Werdenbergstrasse 4, 9471 Buchs, Switzerland
Acknowledgement
The authors gratefully acknowledge the financial support by the Swiss state funding agency CTI (Commission for Technology and Innovation). This work was performed as project CTI 18084.1 “SurfInspect”: Automatic surface inspection of planar and spherical optical components.
©2017 Walter de Gruyter Berlin/Boston
Articles in the same Issue
- Frontmatter
- Editorial
- Forum Bildverarbeitung 2016
- Beiträge
- On the design of a fractal calibration pattern for improved camera calibration
- Compressive shape from focus based on a linear measurement model
- 3D reconstruction by a combined structure tensor and Hough transform light field approach
- Das baryzentrische Verhältnis als Invariante der projektiven Geometrie
- Simulation of microscopic metal surfaces based on measured microgeometry
- Automated surface inspection of small customer-specific optical elements
- Individualisierte optische Messtechnik basierend auf additiv gefertigten optischen Komponenten
- Monokulare Kopfposenschätzung basierend auf dem optischen Fluss und der Verfolgung stabiler Merkmale
- Ein intuitives kamerabasiertes System zur Assistenz sehbehinderter Menschen
Articles in the same Issue
- Frontmatter
- Editorial
- Forum Bildverarbeitung 2016
- Beiträge
- On the design of a fractal calibration pattern for improved camera calibration
- Compressive shape from focus based on a linear measurement model
- 3D reconstruction by a combined structure tensor and Hough transform light field approach
- Das baryzentrische Verhältnis als Invariante der projektiven Geometrie
- Simulation of microscopic metal surfaces based on measured microgeometry
- Automated surface inspection of small customer-specific optical elements
- Individualisierte optische Messtechnik basierend auf additiv gefertigten optischen Komponenten
- Monokulare Kopfposenschätzung basierend auf dem optischen Fluss und der Verfolgung stabiler Merkmale
- Ein intuitives kamerabasiertes System zur Assistenz sehbehinderter Menschen
