Unsupervised colour image segmentation applied to printing quality assessment

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...

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Bibliographic Details
Published in:Image and vision computing 2005-04, Vol.23 (4), p.417-425
Main Authors: Bergman, L., Verikas, A., Bacauskiene, M.
Format: Article
Language:English
Subjects:
Bildanalys
Colour image segmentation
Colour printing
Fuzzy clustering
Image analysis
Information technology
Informationsteknik
Quality inspection
TECHNOLOGY
TEKNIKVETENSKAP
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Summary: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.
ISSN:0262-8856
1872-8138
1872-8138
DOI:10.1016/j.imavis.2004.11.003