Multi-sensory-based pattern recognition in security printing machines

Project Duration: 1.6.2007 to 31.8.2010 (Finished)
Area of Research: Industrial Signal Processing : Sensor fusion, Industrial Signal Processing : Real-time image processing, Industrial Signal Processing : Classification
Project Manager: Prof. Dr.-Ing. Volker Lohweg


During printed product manufacturing, measures are typically taken to ensure a certain level of printing quality. This is particularly true in the field of security printing, where the quality standards, which must be reached by the end-products, are very high, i.e. banknotes, security documents and such like. Quality inspection of printed products is conventionally limited to the optical inspection of the printed product. Usually only the existence or appearance of colours and their textures are checked by an optical inspection system. In general, those mono-modal systems have difficulties in detection of low degradation errors over time. Experienced printing press operators may be capable of identifying degradation or deviation in the printing press behaviour, which could lead to the occurrence of printing errors, for instance characteristic "sounds" produced by the printing press.

Obviously there is a need for an improved inspection system which is not merely restricted to the optical inspection of the printed end-product, but which can take other factors into account than optical quality criteria. A general aim is to improve the known inspection techniques and propose an inspection methodology which can ensure a comprehensive quality control of the printed substrates processed by printing presses, especially printing presses that are designed to process substrates used in the course of the production of banknotes, security documents and such like. Additionally, a second aim is to propose a method, which is suited to be implemented as an expert system designed to facilitate operation of the printing press.

In general, multiple sensors are combined and mounted at a production machine.

One assumption, which is made in such applications, is that the sensor signals should be decorrelated at least in a weak sense. Although, this strategy is conclusive, the main drawback is based on the fact that even experts have only vague information about sensory cross correlation effects in machines or production systems. Furthermore, many measurements which are taken traditionally result in ineffective data simply because the measurement methods are suboptimal.

The research project will highlight new concepts for multi-sensory-based information fusion. 


  • KBA-Giori. S.A. Lausanne
  • Koenig & Bauer AG, Werk Bielefeld - Optische Systeme
  • OWL-Maschinenbau
  • Krause-Biagosch GmbH
  • Chemnitz University of Technology
Image: Multi-sensory-based pattern recognition in security printing machinesImage: Multi-sensory-based pattern recognition in security printing machines


Dyck, Walter; Türke, Thomas; Schaede, Johannes; Lohweg, Volker: A New Concept on Quality Inspection and Machine Conditioning for Security Prints. In: Optical Document Security - The 2008 Conference on Optical Security and Counterfeit Deterrence; Reconnaissance International Publishers and Consultants, San Francisco, CA, USA, Jan 2008 Jan 2008 (More)

Li, Rui; Lohweg, Volker: A Novel Data Fusion Approach using Two-Layer Conflict Solving. In: 2008 IAPR Workshop on Cognitive Information Processing; June 9-10, Santorini, Greece Mar 2008 (More)

Li, Rui; Lohweg, Volker: Fuzzy Pattern Classification Tuning by Parameter Learning based on Fusion Concept. In: The 11th Conference on Information Fusion, June 30 - July 3, Cologne, Germany , Jul 2008 (More)

Lohweg, Volker; Li, Rui; Türke, Thomas; Willeke, Harald; Schaede, Johannes: FPGA-based Multi-sensor Real Time Machine Vision for Banknote Printing. In: 21st annual Symposium on IS&T/SPIE Electronic Imaging, 18 -22 January 2009, San Jose, California USA. Accepted for publication, Jan 2009 (More)


Tobias Christophliemke (Diploma)
Realisierung nichtlinearer Bit-Slice Filter unter Berücksichtigung von Implementierungsaspekten (Details)

Jan-Friedrich Ehlenbröker (Diploma)
Untersuchungen an Kernelfunktionen für Support-Vector-Maschinen (Details)

Alexander Maier (Master)
SVM basierende Fuzzy-Pattern Klassifikation unter besonderer Berücksichtigung problemangepasster Justage (Details)

Alexander Dicks (Diploma)
FPGA-basierendes System-on-Chip zur Klassifikation von Informationen (Details)

Rui Li (Master)
Belief Theory Based Classification (Details)

Denis Petker (Diploma)
Mathematische Modellierung eines adaptiven Fuzzy-Klassifikators unter Berücksichtigung vergleichender Untersuchungen zu dessen Leistungsfähigkeit (Details)

Stefan Glock (Master)
Investigations on Possibilistic Multi-source Data Fusion with Sensor Reliability Monitoring (Details)

Funded by: BMBFGrant ID: 17N1407
Funding: Ingenieurnachwuchs 2007 -Maschinenbau-
Contact Person: Prof. Dr.-Ing. Volker Lohweg , M.Sc. Karl Voth
Research Assistant: M.Sc. Karl Voth
Dokumente: Projekt_des_Monats_Juni_2008.pdf