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Bergman, Lars
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Publications (10 of 13) Show all publications
Verikas, A., Malmqvist, K. & Bergman, L. (2005). Detecting and measuring rings in banknote images. Engineering applications of artificial intelligence, 18(3), 363-371
Open this publication in new window or tab >>Detecting and measuring rings in banknote images
2005 (English)In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 18, no 3, p. 363-371Article in journal (Refereed) Published
Abstract [en]

Various intelligent systems show a rapidly growing potential use of visual information processing technologies. This paper presents an example of employing visual information processing technologies for detecting and measuring rings in banknote images. The size of the rings is one of parameters used to inspect the banknote printing quality. The approach developed consists of two phases. In the first phase, based on histogram processing and data clustering, image areas containing rings are localized and edges of the rings are detected. Then, in the second phase, applying the hard and possibilistic spherical shell clustering to the extracted edge pixels the ring centre and radii are estimated. The experimental investigations performed have shown that even highly occluded rings are robustly detected. Several prototypes of the system developed have been installed in two banknote printing shops in Europe.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2005
Keywords
Quality inspection, Colour image processing, Fuzzy clustering, Histogram processing
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hh:diva-261 (URN)10.1016/j.engappai.2004.09.014 (DOI)000228264400010 ()2-s2.0-14844285749 (Scopus ID)2082/556 (Local ID)2082/556 (Archive number)2082/556 (OAI)
Available from: 2006-11-24 Created: 2006-11-24 Last updated: 2018-03-23Bibliographically approved
Bergman, L., Verikas, A. & Bacauskiene, M. (2005). Unsupervised colour image segmentation applied to printing quality assessment. Image and Vision Computing, 23(4), 417-425
Open this publication in new window or tab >>Unsupervised colour image segmentation applied to printing quality assessment
2005 (English)In: Image and Vision Computing, ISSN 0262-8856, E-ISSN 1872-8138, Vol. 23, no 4, p. 417-425Article in journal (Refereed) Published
Abstract [en]

We present an option for colour image segmentation applied to printing quality assessment in offset lithographic printing by measuring an average ink dot size in halftone pictures. The segmentation is accomplished in two stages through classification of image pixels. In the first stage, rough image segmentation is performed. The results of the first segmentation stage are then utilized to collect a balanced training data set for learning refined parameters of the decision rules. The developed software is successfully used in a printing shop to assess the ink dot size on paper and printing plates.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2005
Keywords
Colour image segmentation, Fuzzy clustering, Quality inspection, Colour printing
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:hh:diva-259 (URN)10.1016/j.imavis.2004.11.003 (DOI)000227222100005 ()2-s2.0-13444278799 (Scopus ID)2082/554 (Local ID)2082/554 (Archive number)2082/554 (OAI)
Available from: 2006-11-24 Created: 2006-11-24 Last updated: 2018-03-23Bibliographically approved
Bergman, L. (2005). Using multicoloured halftone screens for offset print quality monitoring. (Licentiate dissertation). Linköping: Linköping University Electronic Press
Open this publication in new window or tab >>Using multicoloured halftone screens for offset print quality monitoring
2005 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

In the newspaper printing industry, offset is the dominating printing method and the use of multicolour printing has increased rapidly in newspapers during the last decade. The offset printing process relies on the assumption that an uniform film of ink of right thickness is transferred onto the printing areas. The quality of reproduction of colour images in offset printing is dependent on a number of parameters in a chain of steps and in the end it is the amount and the distribution of ink deposited on the substrate that create the sensation and thus the perceived colours. We identify three control points in the offset printing process and present methods for assessing the printing process quality in two of these points:

• Methods for determining if the printing plates carry the correct image

• Methods for determining the amount of ink deposited onto the newsprint

A new concept of colour impression is introduced as a measure of the amount of ink deposited on the newsprint. Two factors contribute to values of the colour impression, the halftone dot-size and ink density. Colour impression values are determined on gray-bars using a CCD-camera based system. Colour impression values can also be determined in an area containing an arbitrary combination of cyan magenta and yellow inks. The correct amount of ink is known either from a reference print or from prepress information. Thus, the deviation of the amount of ink can be determined that can be used as control value by a press operator or as input to a control system.

How a closed loop controller can be designed based on the colour impression values is also shown.

It is demonstrated that the methods developed can be used for off-line print quality monitoring and ink feed control, or preferably in an online system in a newspaper printing press.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2005. p. 48
Series
Linköping studies in science and technology. Licentiate thesis, ISSN 0280-7971 ; 1147
Keywords
Multicolour printing, Printing process, Colour images, Colour impression, CCD-camera
National Category
Computer Engineering
Identifiers
urn:nbn:se:hh:diva-713 (URN)2082/1062 (Local ID)91-85297-25-9 (ISBN)2082/1062 (Archive number)2082/1062 (OAI)
Presentation
2005-02-10, 00:00 (English)
Supervisors
Note

Report code: LiU-TEK-LIC-2005:02

Available from: 2007-06-04 Created: 2007-06-04 Last updated: 2018-03-23Bibliographically approved
Bergman, L. & Verikas, A. (2004). Intelligent Monitoring of the Offset Printing Process. In: Proceedings of the IASTED International Conference on Neural Networks and Computational Intelligence: . Paper presented at International Conference on Neural Networks and Computational Intelligence, Grindelwald, 23 - 25 February 2004 (pp. 173-178). ACTA Press
Open this publication in new window or tab >>Intelligent Monitoring of the Offset Printing Process
2004 (English)In: Proceedings of the IASTED International Conference on Neural Networks and Computational Intelligence, ACTA Press, 2004, p. 173-178Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we present a neural networks and image analysis based approach to assessing colour deviations in an offset printing process from direct measurements on halftone multicoloured pictures--there are no measuring areas printed solely to assess the deviations. A committee of neural networks is trained to assess the ink proportions in a small image area. From only one measurement the trained committee is capable of estimating the actual amount of printing inks dispersed on paper in the measuring area. To match the measured image area of the printed picture with the corresponding area of the original image, when comparing the actual ink proportions with the targeted ones, properties of the 2-D Fourier transform are exploited.

Place, publisher, year, edition, pages
ACTA Press, 2004
Keywords
Neural modelling, Neural network committee, Fourier transform, Offset lithographic printing
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:hh:diva-19714 (URN)000228458400031 ()2-s2.0-11144340833 (Scopus ID)
Conference
International Conference on Neural Networks and Computational Intelligence, Grindelwald, 23 - 25 February 2004
Note

Article number 413-065

Available from: 2012-09-24 Created: 2012-09-24 Last updated: 2018-03-29Bibliographically approved
Verikas, A., Malmqvist, K., Bergman, L. & Engstrand, P. (2003). Colour speck counter for assessing the dirt level in secondary fibre pulps. Journal of Pulp and Paper Science (JPPS), 29(7), 220-224
Open this publication in new window or tab >>Colour speck counter for assessing the dirt level in secondary fibre pulps
2003 (English)In: Journal of Pulp and Paper Science (JPPS), ISSN 0826-6220, Vol. 29, no 7, p. 220-224Article in journal (Refereed) Published
Abstract [en]

Speck count is increasingly used as a parameter to assess the quality of secondary fibre pulps. The resolution of most of the commercial image analysis systems is too low for detecting small specks. Therefore, small specks are not taken into consideration when using conventional image analysis systems to assess pulp quality. We have recently developed a colour speck counter which can detect specks ranging in size from ∼5 to 300 μm. In this paper, we present the results of experimental investigations related to the use of the speck counter to assess the dirt level in secondary fibre pulps. We assume an exponential speck size distribution and advocate the idea of using the scale parameter λ of the distribution to characterize the size content of a set of specks detected. Experimental investigations performed have shown that the scale parameter, together with the expected speck area and the speck number, can be used to characterize and rank secondary fibre pulps according to dirt level and the dirt-size distribution.

Place, publisher, year, edition, pages
Montreal: Pulp and Paper Technical Association of Canada, 2003
Keywords
Dirt count, Machine design, Image analysis, Measuring instruments, Reclaimed fibers
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hh:diva-217 (URN)000185031700002 ()2-s2.0-0142059189 (Scopus ID)2082/512 (Local ID)2082/512 (Archive number)2082/512 (OAI)
Available from: 2006-11-24 Created: 2006-11-24 Last updated: 2018-03-23Bibliographically approved
Bergman, L., Verikas, A., Englund, C., Kindberg, J., Olsson, J. & Sjögren, B. (2003). Modelling and Control of the Web-Fed Offset Newspaper Printing Press. In: Proceedings of the Technical Association of the Graphic Arts, TAGA: . Paper presented at 2003 Proceedings-Technical Associations of the Graphic Arts, TAGA, Montreal, Canada (pp. 27-29). Technical Association of the Graphic (TAGA)
Open this publication in new window or tab >>Modelling and Control of the Web-Fed Offset Newspaper Printing Press
Show others...
2003 (English)In: Proceedings of the Technical Association of the Graphic Arts, TAGA, Technical Association of the Graphic (TAGA) , 2003, p. 27-29Conference paper, Published paper (Refereed)
Abstract [en]

We present an approach to modelling and controlling the web-fed offset printing process. An image processing and artificial neural networks based device is used to measure the printing process output - the observable variables. The observable variables are measured on halftone areas and integrate information about both ink densities and dot sizes. From only one measurement the device is capable of estimating the actual relative amount of each cyan, magenta, yellow, and black ink dispersed on paper in the measuring area. We build and test linear and non-linear printing press models using the measured variables andother parameters characterising the press. The observable variables measured and the press model developed are then further used by a control unit for generating control signals - signals for controlling the ink keys - to compensate for colour deviation. The experimental investigations performed have shown that the non-linear model developed is accurate enough to be used in a control loop for controlling the printing process. The control accuracy - the tracking accuracy of the desired ink level - obtained from the controller was higher than that observed when controlling the press by the operator.

Place, publisher, year, edition, pages
Technical Association of the Graphic (TAGA), 2003
Keywords
Colour control, Neural network, Newsprint
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hh:diva-19715 (URN)2-s2.0-1942421673 (Scopus ID)
Conference
2003 Proceedings-Technical Associations of the Graphic Arts, TAGA, Montreal, Canada
Available from: 2012-09-24 Created: 2012-09-24 Last updated: 2018-03-22Bibliographically approved
Verikas, A., Malmqvist, K., Bacauskiene, M. & Bergman, L. (2000). Monitoring the de-inking process through neural network-based colour image analysis. Neural computing & applications (Print), 9(2), 142-151
Open this publication in new window or tab >>Monitoring the de-inking process through neural network-based colour image analysis
2000 (English)In: Neural computing & applications (Print), 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
Keywords
Classification, Colour image processing, Fuzzy sets, Neural networks, Self-organising map, Classifier networks, Graphic arts, Fuzzy, Segmentation
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hh:diva-3544 (URN)10.1007/s005210070025 (DOI)000088547900009 ()2-s2.0-0034336492 (Scopus ID)
Available from: 2010-01-13 Created: 2009-12-01 Last updated: 2018-03-23Bibliographically approved
Verikas, A., Malmqvist, K. & Bergman, L. (2000). Neural networks based colour measuring for process monitoring and control in multicoloured newspaper printing. Neural computing & applications (Print), 9(3), 227-242
Open this publication in new window or tab >>Neural networks based colour measuring for process monitoring and control in multicoloured newspaper printing
2000 (English)In: Neural computing & applications (Print), ISSN 0941-0643, E-ISSN 1433-3058, Vol. 9, no 3, p. 227-242Article in journal (Refereed) Published
Abstract [en]

This paper presents a neural networks based method and a system for colour measurements on printed halftone multicoloured pictures and halftone multicoloured bars in newspapers. The measured values, called a colour vector, are used by the operator controlling the printing process to make appropriate ink feed adjustments to compensate for colour deviations of the picture being measured from the desired print. By the colour vector concept, we mean the CMY or CMYK (cyan, magenta, yellow and black) vector, which lives in the three- or four-dimensional space of printing inks. Two factors contribute to values of the vector components, namely the percentage of the area covered by cyan, magenta, yellow and black inks (tonal values) and ink densities. Values of the colour vector components increase if tonal values or ink densities rise, and vice versa. If some reference values of the colour vector components are set from a desired print, then after an appropriate calibration, the colour vector measured on an actual halftone multicoloured area directly shows how much the operator needs to raise or lower the cyan, magenta, yellow and black ink densities to compensate for colour deviation from the desired print. The 18 months experience of the use of the system in the printing shop witnesses its usefulness through the improved quality of multicoloured pictures, the reduced consumption of inks and, therefore, less severe problems of smearing and printing through.

Place, publisher, year, edition, pages
London: Springer, 2000
Keywords
Colour classification, Colour printing, Decision fusion, Graphic arts, Neural networks, Classifiers, Combination, Regression, Estimators
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:hh:diva-3545 (URN)10.1007/s005210070016 (DOI)000090150400009 ()2-s2.0-0034344209 (Scopus ID)
Available from: 2010-01-13 Created: 2009-12-01 Last updated: 2018-03-23Bibliographically approved
Verikas, A., Malmqvist, K., Malmqvist, L. & Bergman, L. (1999). A New method for colour measurements in graphic arts. Color Research and Application, 24(3), 185-196
Open this publication in new window or tab >>A New method for colour measurements in graphic arts
1999 (English)In: Color Research and Application, ISSN 0361-2317, E-ISSN 1520-6378, Vol. 24, no 3, p. 185-196Article in journal (Refereed) Published
Abstract [en]

This article presents a method for colour measurements directly on printed half-tone multicoloured pictures. The article introduces the concept of colour impression. By this concept we mean the CMY or CMYK vector (colour vector), which lives in the three- or four-dimensional space of printing inks. Two factors contribute to values of the vector components, namely, the percentage of the area covered by cyan, magenta, yellow, and black inks (tonal values) and ink densities. The colour vector expresses integrated information about the tonal values and ink densities. Values of the colour vector components increase if tonal values or ink densities rise and vice versa. If, for some primary colour, the ink density and tonal value do not change, the corresponding component of the colour vector remains constant. If some reference values of the colour vector components are set from a preprint, then, after an appropriate calibration, the colour vector directly shows how much the operator needs to raise or lower the cyan, magenta, yellow, and black ink densities in order to correct colours of the picture being measured. The values of the components are obtained by registering the RGB image from the measuring area and then transforming the set of registered RGB values to the triplet or quadruple of CMY or CMYK values, respectively. Algorithms based on artificial neural networks are used for performing the transformation. During the experimental investigations, we have found a good correlation between components of the colour vector and ink densities.

Place, publisher, year, edition, pages
New York: Wiley-Blackwell, 1999
Keywords
Colorimetry, Calibration, Color printing, Ink, Neural networks, Vectors, Colour classification, Graphic arts
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hh:diva-3546 (URN)10.1002/(SICI)1520-6378(199906)24:3<185::AID-COL5>3.0.CO;2-1 (DOI)000079957400003 ()2-s2.0-0032688107 (Scopus ID)
Available from: 2010-01-13 Created: 2009-12-01 Last updated: 2018-03-23Bibliographically approved
Verikas, A., Malmqvist, K., Bergman, L. & Signahl, M. (1998). Colour classification by neural networks in graphic arts. Neural computing & applications (Print), 7(1), 52-64
Open this publication in new window or tab >>Colour classification by neural networks in graphic arts
1998 (English)In: Neural computing & applications (Print), ISSN 0941-0643, E-ISSN 1433-3058, Vol. 7, no 1, p. 52-64Article in journal (Refereed) Published
Abstract [en]

This paper presents a hierarchical modular neural network for colour classification in graphic arts, capable of distinguishing among very Similar colour classes. The network performs analysis in a rough to fine fashion, and is able to achieve a high average classification speed and a low classification error. In the rough stage of the analysis, clusters of highly overlapping colour classes are detected Discrimination between such colour classes is performed in the next stage by using additional colour information from the surroundings of the pixel being classified. Committees of networks make decisions in the next stage. Outputs of members of the committees are adaptively fused through the BADD defuzzification strategy or the discrete Choquet fuzzy integral. The structure of the network is automatically established during the training process. Experimental investigations show the capability of the network to distinguish among very similar colour classes that can occur in multicoloured printed pictures. The classification accuracy obtained is sufficient for the network to be used for inspecting the quality of multicoloured prints.

Place, publisher, year, edition, pages
London: Springer London, 1998
Keywords
classification, colour image processing, fuzzy integral, modular neural networks, neural fuzzy system
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hh:diva-18802 (URN)10.1007/BF01413709 (DOI)000075763100006 ()2-s2.0-0032343391 (Scopus ID)
Available from: 2012-07-05 Created: 2012-06-25 Last updated: 2018-03-22Bibliographically approved
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