Unsupervised colour image segmentation applied to printing quality assessment
2005 (English)In: Image and Vision Computing, ISSN 0262-8856, Vol. 23, no 4, 417-425 p.Article in journal (Refereed) Published
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
2005. Vol. 23, no 4, 417-425 p.
Colour image segmentation; Fuzzy clustering; Quality inspection; Colour printing
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-13768DOI: 10.1016/j.imavis.2004.11.003OAI: oai:DiVA.org:liu-13768DiVA: diva2:21382