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Monitoring the de-inking process through neural network-based colour image analysis
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0003-2185-8973
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
Department of Applied Electronics, Kaunas University of Technology, Kaunas, Lithuania .
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
2000 (English)In: Neural Computing & Applications, ISSN 0941-0643, E-ISSN 1433-3058, Vol. 9, no 2, p. 142-151Article in journal (Refereed) Published
Abstract [en]

This paper presents an approach to determining the colours of specks in an image of a pulp being recycled. The task is solved through colour classification by an artificial neural network. The network is trained using fuzzy possibilistic target values. The number of colour classes found in the images is determined through the self-organising process in the two-dimensional self-organising map. The experiments performed have shown that the colour classification results correspond well with human perception of the colours of the specks.

Place, publisher, year, edition, pages
New York, USA: Springer-Verlag New York, 2000. Vol. 9, no 2, p. 142-151
Keywords [en]
Classification, Colour image processing, Fuzzy sets, Neural networks, Self-organising map, Classifier networks, Graphic arts, Fuzzy, Segmentation
National Category
Clinical Medicine Educational Sciences
Identifiers
URN: urn:nbn:se:hh:diva-3544DOI: 10.1007/s005210070025ISI: 000088547900009Scopus ID: 2-s2.0-0034336492OAI: oai:DiVA.org:hh-3544DiVA, id: diva2:285828
Available from: 2010-01-13 Created: 2009-12-01 Last updated: 2022-09-13Bibliographically approved

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Verikas, AntanasMalmqvist, KerstinBergman, Lars

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  • apa
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  • en-US
  • fi-FI
  • nn-NO
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Output format
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