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Spectral Imaging: How to select the most suitable technology for your application -
A short course on performance, pitfalls and best practice
Learn how to:
- define robustness and select the most appropriate spectrometer technology for your appication
- specify and calibrate your instrument to obtain the best performance
- optimize your optical setup and system calibration procedure for inline control: figures of merit
- sampling and present the sample
- analyze opaque and scattering systems
Prof. em. Dr. Rudolf W. Kessler
Head of Steinbeis Technology Transfer Center
on Process Control and Data Analysis
Dr. Rudolf W. Kessler is a Professor Emeritus of Chemistry at Reutlingen University, Germany. After his studies in Chemistry and his PhD in spectroscopy, he worked for some years with Mercedes Benz at the basic research department in Stuttgart, Germany. At present, he is head of a Steinbeis Technology Transfer Center on Process Control and Data Analysis. His main research areas are in process analysis and chemical imaging. He has published a book on process analysis and has a high record of many peer reviewed papers, contributions for conferences and he owns several patents. He implemented several online and inline systems in industry during the last 30 years and also works as a consultant for knowledge based manufacturing.
As a co-founder of the process analysis group of the German Chemical Society (GDCh) and DECHEMA, as its chairman from 2009 – 2012 and as well as a member of the board, he established together with his colleagues a strong PAT-network in Germany and Europe and he is also one of the organizers of the EuroPact conferences. Recently, he initiated and established a centre of excellence for research and education: “Process Analysis & Technology, PA&T” and an international Master of Science in "Process Analysis & Technology Management” at Reutlingen University, Germany. In September 2014 he retired as a full professor but is still active in technology transfer.
Analysis of Hyperspectral Images by Multivariate Data Analysis
- Principal Component Analysis (PCA) for images
- The PCA model, what are scores, what are loadings
- Finding structures in images by means of PCA
- Knowledge extraction from images by means of PCA
- Introduction to quantitative analysis for images
Prof. Dipl. Phys. Waltraud Kessler
Managing Director of the Steinbeis Technology Transfer Center
on multivariate Data Analysis.
Honorary Professor at Reutlingen Univer
Prof. Waltraud Kessler has a degree in physics and worked several years as a software developer especially for process control and data analysis. At the Institute of Applied Research at Reutlingen University (Germany) she planned and conducted research work within European projects in the field of Process Analytical Technologies (PAT). Her main focus has been the knowledge extraction from big data bases in particular spectroscopic data by using multivariate data analysis. The results have been published in many scientific publications and industrial patents. In 2007 she wrote a German textbook on multivariate data analysis with the German title “Multivariate Datenanalyse für die Pharma- Bio- und Prozessanalytik”.
Professor Kessler started teaching experimental design and multivariate data analysis for chemical engineers at the chemistry department of Reutlingen University in the early nineties and was appointed Honorary Professor in 2002. Her current lectures at Reutlingen and other universities are on experimental design and multivariate data analysis. She is Managing Director of the Steinbeis-Transfer-Institut Multivariate Daten Analyse and is engaged in the working party PAT (Process analytical technology) of the European Pharmacopoeia Commission.
Hyperspectral Imaging in Industry
- Hyperspectral data and preprocessing
- Feature based processing
- Chemical Color Imaging
- Industrial application
- Modular hyperspectral processing
DI (FH) Markus Burgstaller
CEO, Head of R&D at
Perception Park GmbH
Markus Burgstaller received his M.S. degree in electronics from the Carinthia University of Applied Science in 2002. After 2 years in the field of robot vision at Joanneum Research GmbH as well as freelancer, he started with Hyperspectral Imaging at EVK DI Kerschhaggl GmbH in 2006. After development of the first smart hyperspectral camera system he led the hyperspectral product development and later on the R&D team at EVK.
In 2012 Markus founded Perception Park with the aim to introduce the high potential hyperspectral technology to the broad industrial market. Perception Park is focused solely on data processing solutions based on the first generic, intuitive understandable and free configurable data processing platform for the industrial application of hyperspectral imaging.
Machine Learning and Hyperspectral Imaging
This introduction will cover the basic methods from pattern recognition and machine learning that are commonly used in Hyperspectral imaging, it will cover supervised (LDA, SVM, etc.) and unsupervised (PCA, Clustering etc.) methods. The main emphasize will be on methods that are used in practice.
Prof. Dr. Horst Bischof
Vice Rector Research
Graz University of Technology
Institute for Computer Graphics and Vision
Horst Bischof received his M.S. and Ph.D. degree in computer science from the Vienna University of Technology in 1990 and 1993, respectively. In 1998 he got his Habilitation (venia docendi) for applied computer science. Currently he is Vice Rector for Research at Graz University of Technology and Professor at the Institute for Computer Graphics and Vision at the Graz University of Technology, Austria. H. Bischof is member of the scientific board of Joanneum Research. H. Bischof is board member of the Fraunhofer Inst. für Graphische Datenverarbeitung (IGD). His research interests include object recognition, visual learning, motion and tracking, visual surveillance and biometrics, medical computer vision, and adaptive methods for computer vision where he has published more than 630 peer reviewed scientific papers.
Horst Bischof if General Chair of CVPR 2015 and was chairman of the DAGM/ÖAGM conferene 2012 and co-chairman of international conferences (ICANN, DAGM), and local organizer for ICPR'96. He was program co-chair of ECCV2006 and several times Area chair of all major vision conferences. Currently he is Associate Editor for IEEE Trans. on Pattern Analysis and Machine Intelligence, Pattern Recognition, Computer and Informatics and the Journal of Universal Computer Science.
Horst Bischof is member of the European academy of sciences and has received several (19) awards among them the 29th Pattern Recognition award in 2002; the main price of the German Association for Pattern Recognition DAGM in 2007 and 2012, the Best scientific paper award at the BMCV 2007, and the BMVC best demo award 2012 and the Best scientific paper awards at the ICPR 2008, ICPR2010, PCV 2010, AAPR2010 and ACCV 2012.