---
_id: '2075'
abstract:
- lang: eng
text: Automatic sheet inspection in banknote production has been used as a standard
quality control tool for more than a decade. As more and more print techniques
and new security features are established, total quality in bank note printing
must be guaranteed. This aspect has a direct impact on the research and development
for bank note inspection systems in general in the sense of technological sustainability.
It is accepted, that print defects are generated not only by printing parameter
changes, but also by mechanical machine parameter changes, which will change unnoticed
in production. Therefore, a new concept for a multi-sensory adaptive learning
and classification model based on Fuzzy-Pattern- Classifiers for data inspection
and machine conditioning is proposed. A general aim is to improve the known inspection
techniques and propose an inspection methodology that can ensure a comprehensive
quality control of the printed substrates processed by printing presses, especially
printing presses which are designed to process substrates used in the course of
the production of banknotes, security documents and others. Therefore, the research
and development work in this area necessitates a change in concept for banknote
inspection in general. In this paper a new generation of FPGA (Field Programmable
Gate Array) based real time inspection technology is presented, which allows not
only colour inspection on banknote sheets, but has also the implementation flexibility
for various inspection algorithms for security features, such as window threads,
embedded threads, OVDs, watermarks, screen printing etc., and multi-sensory data
processing. A variety of algorithms is described in the paper, which are designed
for and implemented on FPGAs. The focus is based on algorithmic approaches
author:
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
- first_name: Rui
full_name: Li, Rui
id: '2000'
last_name: Li
- first_name: Thomas
full_name: Türke, Thomas
last_name: Türke
- first_name: Harald
full_name: Willeke, Harald
last_name: Willeke
- first_name: Johannes
full_name: Schaede, Johannes
id: '2128'
last_name: Schaede
citation:
ama: 'Lohweg V, Li R, Türke T, Willeke H, Schaede J. FPGA-based Multi-sensor Real
Time Machine Vision for Banknote Printing. In: 21st Annual Symposium on IST/SPIE
Electronic Imaging, 18 -22 January 2009,. San Jose, California USA. Accepted
for publication; 2009. doi:https://doi.org/10.1117/12.805427'
apa: Lohweg, V., Li, R., Türke, T., Willeke, H., & Schaede, J. (2009). FPGA-based
Multi-sensor Real Time Machine Vision for Banknote Printing. In 21st annual
Symposium on IST/SPIE Electronic Imaging, 18 -22 January 2009,. San Jose,
California USA. Accepted for publication. https://doi.org/10.1117/12.805427
bjps: Lohweg V et al. (2009) FPGA-Based Multi-Sensor Real Time Machine
Vision for Banknote Printing. 21st Annual Symposium on IST/SPIE Electronic
Imaging, 18 -22 January 2009,. San Jose, California USA. Accepted for publication.
chicago: Lohweg, Volker, Rui Li, Thomas Türke, Harald Willeke, and Johannes Schaede.
“FPGA-Based Multi-Sensor Real Time Machine Vision for Banknote Printing.” In 21st
Annual Symposium on IST/SPIE Electronic Imaging, 18 -22 January 2009,. San
Jose, California USA. Accepted for publication, 2009. https://doi.org/10.1117/12.805427.
chicago-de: 'Lohweg, Volker, Rui Li, Thomas Türke, Harald Willeke und Johannes Schaede.
2009. FPGA-based Multi-sensor Real Time Machine Vision for Banknote Printing.
In: 21st annual Symposium on IST/SPIE Electronic Imaging, 18 -22 January 2009,.
San Jose, California USA. Accepted for publication. doi:https://doi.org/10.1117/12.805427,
.'
din1505-2-1: '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 IST/SPIE Electronic Imaging, 18 -22 January 2009,. San Jose,
California USA. Accepted for publication, 2009'
havard: 'V. Lohweg, R. Li, T. Türke, H. Willeke, J. Schaede, FPGA-based Multi-sensor
Real Time Machine Vision for Banknote Printing, in: 21st Annual Symposium on IST/SPIE
Electronic Imaging, 18 -22 January 2009, San Jose, California USA. Accepted for
publication, 2009.'
ieee: V. Lohweg, R. Li, T. Türke, H. Willeke, and J. Schaede, “FPGA-based Multi-sensor
Real Time Machine Vision for Banknote Printing,” in 21st annual Symposium on
IST/SPIE Electronic Imaging, 18 -22 January 2009, 2009.
mla: Lohweg, Volker, et al. “FPGA-Based Multi-Sensor Real Time Machine Vision for
Banknote Printing.” 21st Annual Symposium on IST/SPIE Electronic Imaging, 18
-22 January 2009, 2009, doi:https://doi.org/10.1117/12.805427.
short: 'V. Lohweg, R. Li, T. Türke, H. Willeke, J. Schaede, in: 21st Annual Symposium
on IST/SPIE Electronic Imaging, 18 -22 January 2009, San Jose, California USA.
Accepted for publication, 2009.'
ufg: 'Lohweg, Volker et. al. (2009): FPGA-based Multi-sensor Real Time Machine
Vision for Banknote Printing, in: 21st annual Symposium on IST/SPIE Electronic
Imaging, 18 -22 January 2009,, San Jose, California USA. Accepted for publication.'
van: 'Lohweg V, Li R, Türke T, Willeke H, Schaede J. FPGA-based Multi-sensor Real
Time Machine Vision for Banknote Printing. In: 21st annual Symposium on IST/SPIE
Electronic Imaging, 18 -22 January 2009,. San Jose, California USA. Accepted for
publication; 2009.'
date_created: 2019-11-29T14:33:24Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
doi: https://doi.org/10.1117/12.805427
language:
- iso: eng
main_file_link:
- url: https://www.spiedigitallibrary.org/conference-proceedings-of-spie/7251/72510S/FPGA-based-multisensor-real-time-machine-vision-for-banknote-printing/10.1117/12.805427.full
place: San Jose, California USA. Accepted for publication
publication: 21st annual Symposium on IST/SPIE Electronic Imaging, 18 -22 January
2009,
publication_status: published
status: public
title: FPGA-based Multi-sensor Real Time Machine Vision for Banknote Printing
type: conference
user_id: '45673'
year: 2009
...
---
_id: '2070'
abstract:
- lang: eng
text: 'A Two-Layer Conflict Solving data fusion approach is proposed in this work,
with an aim to provide another approach to data fusion community. Since the evidence
of Dempster-Shafer Theory, algorithms for combining pieces of evidence have drawn
a considerable attention from data fusion researchers, along with many alternatives
invented. However, none of these approaches receive an agreement for being able
to perform very successfully in all scenarios and hence this topic is still in
hot discussion. Therefore, the suggested approach in this work will contribute
as a novel method and present its own merits. '
author:
- first_name: Rui
full_name: Li, Rui
id: '2000'
last_name: Li
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
citation:
ama: 'Li R, Lohweg V. A Novel Data Fusion Approach using Two-Layer Conflict Solving.
In: ; 2008.'
apa: Li, R., & Lohweg, V. (2008). A Novel Data Fusion Approach using Two-Layer
Conflict Solving.
bjps: Li R and Lohweg V (2008) A Novel Data Fusion Approach Using Two-Layer
Conflict Solving.
chicago: Li, Rui, and Volker Lohweg. “A Novel Data Fusion Approach Using Two-Layer
Conflict Solving,” 2008.
chicago-de: 'Li, Rui und Volker Lohweg. 2008. A Novel Data Fusion Approach using
Two-Layer Conflict Solving. In: .'
din1505-2-1: 'Li, Rui ; Lohweg,
Volker: A Novel Data Fusion Approach using Two-Layer Conflict Solving.
In: , 2008'
havard: 'R. Li, V. Lohweg, A Novel Data Fusion Approach using Two-Layer Conflict
Solving, in: 2008.'
ieee: R. Li and V. Lohweg, “A Novel Data Fusion Approach using Two-Layer Conflict
Solving,” 2008.
mla: Li, Rui, and Volker Lohweg. A Novel Data Fusion Approach Using Two-Layer
Conflict Solving. 2008.
short: 'R. Li, V. Lohweg, in: 2008.'
ufg: 'Li, Rui/Lohweg, Volker (2008): A Novel Data Fusion Approach using Two-Layer
Conflict Solving, in: .'
van: Li R, Lohweg V. A Novel Data Fusion Approach using Two-Layer Conflict Solving.
In 2008.
date_created: 2019-11-29T14:05:44Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
keyword:
- fusion community
- data fusion researcher
- dempster-shafer theory
- many alternative
- novel method
- considerable attention
- hot discussion
- suggested approach
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.eurasip.org/Proceedings/Ext/CIP2008/papers/1569094849.pdf
oa: '1'
publication_status: published
status: public
title: A Novel Data Fusion Approach using Two-Layer Conflict Solving
type: conference
user_id: '45673'
year: 2008
...
---
_id: '2071'
abstract:
- lang: eng
text: In this paper, a fuzzy pattern classification tuning approach is proposed,
which is based on fusion concept. In this method, tuning parameters are learned
in a training procedure, enabling system to be capable of managing individual
classification task. Fuzzy c-means, as a specific instance of Tuning Reference,
is employed as a tool to offer membership function which is used for making decisions
and its membership function fuses (tunes) another membership function captured
from fuzzy pattern classification and then final decisions are made upon fused
one. Experiments are taken on five benchmark datasets, one of them shows an equal
performance and the other four present better results than each single classifier.
author:
- first_name: Rui
full_name: Li, Rui
id: '2000'
last_name: Li
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
citation:
ama: 'Li R, Lohweg V. Fuzzy Pattern Classification Tuning by Parameter Learning
based on Fusion Concept. In: In: The 11th Conference on Information Fusion, June
30 - July 3, Cologne, Germany; 2008.'
apa: 'Li, R., & Lohweg, V. (2008). Fuzzy Pattern Classification Tuning by Parameter
Learning based on Fusion Concept. In: The 11th Conference on Information Fusion,
June 30 - July 3, Cologne, Germany.'
bjps: 'Li R and Lohweg V (2008) Fuzzy Pattern Classification Tuning by Parameter
Learning Based on Fusion Concept. In: The 11th Conference on Information Fusion,
June 30 - July 3, Cologne, Germany.'
chicago: 'Li, Rui, and Volker Lohweg. “Fuzzy Pattern Classification Tuning by Parameter
Learning Based on Fusion Concept.” In: The 11th Conference on Information Fusion,
June 30 - July 3, Cologne, Germany, 2008.'
chicago-de: 'Li, Rui und Volker Lohweg. 2008. Fuzzy Pattern Classification Tuning
by Parameter Learning based on Fusion Concept. In: . In: The 11th Conference on
Information Fusion, June 30 - July 3, Cologne, Germany.'
din1505-2-1: 'Li, Rui ; Lohweg,
Volker: Fuzzy Pattern Classification Tuning by Parameter Learning based
on Fusion Concept. In: : In: The 11th Conference on Information Fusion, June
30 - July 3, Cologne, Germany, 2008'
havard: 'R. Li, V. Lohweg, Fuzzy Pattern Classification Tuning by Parameter Learning
based on Fusion Concept, in: In: The 11th Conference on Information Fusion, June
30 - July 3, Cologne, Germany, 2008.'
ieee: R. Li and V. Lohweg, “Fuzzy Pattern Classification Tuning by Parameter Learning
based on Fusion Concept,” 2008.
mla: 'Li, Rui, and Volker Lohweg. Fuzzy Pattern Classification Tuning by Parameter
Learning Based on Fusion Concept. In: The 11th Conference on Information Fusion,
June 30 - July 3, Cologne, Germany, 2008.'
short: 'R. Li, V. Lohweg, in: In: The 11th Conference on Information Fusion, June
30 - July 3, Cologne, Germany, 2008.'
ufg: 'Li, Rui/Lohweg, Volker (2008): Fuzzy Pattern Classification Tuning
by Parameter Learning based on Fusion Concept, in: .'
van: 'Li R, Lohweg V. Fuzzy Pattern Classification Tuning by Parameter Learning
based on Fusion Concept. In In: The 11th Conference on Information Fusion, June
30 - July 3, Cologne, Germany; 2008.'
date_created: 2019-11-29T14:09:33Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
keyword:
- tuning parameter
- information fusion
- fuzzy cmeans
- membership function
- fuzzy pattern classification
language:
- iso: eng
main_file_link:
- url: https://ieeexplore.ieee.org/document/4632223/keywords#full-text-header
publication_identifier:
isbn:
- 978-3-8007-3092-6
publication_status: published
publisher: 'In: The 11th Conference on Information Fusion, June 30 - July 3, Cologne,
Germany'
status: public
title: Fuzzy Pattern Classification Tuning by Parameter Learning based on Fusion Concept
type: conference
user_id: '45673'
year: 2008
...