Publications:Unsupervised colour image segmentation applied to printing quality assessment

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Title Unsupervised colour image segmentation applied to printing quality assessment
Author Lars Bergman and Antanas Verikas and M. Bacauskiene
Year 2005
PublicationType Journal Paper
Journal Image and Vision Computing
HostPublication
Conference
DOI http://dx.doi.org/10.1016/j.imavis.2004.11.003
Diva url http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:237438
Abstract 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.