Semi-automatic identification of print layers from a sequence of sample images: A case study from banknote print inspection

Daniel Soukup, Ulrich Bodenhofer, Markus Mittendorfer-Holzer, Konrad Mayer

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

This article presents an approach for finding displacements of print layers from sequences of sample images semi-automatically with the aim to simplify and shorten the setup of inspection systems for printing processes in which the perfect alignment of print layers cannot be guaranteed. The basic idea behind the proposed approach is to identify pixels which are likely to have the same displacements for a given pair of images. This relatively coarse information is computed for several pairs of sample images and aggregated in order to identify regions that tend to have the same displacement over a large proportion of image pair comparisons. This idea is motivated and justified in detail. The test cases considered in this study are data from banknote print inspection. We use these data to illustrate the steps of the algorithm. The examples demonstrate the method's capability to sensibly identify print layers, even if they overlap partially. Although the paper concentrates on a particular case study, the method can be used in any print inspection process with similar characteristics.

Original languageEnglish
Pages (from-to)989-998
Number of pages10
JournalImage and Vision Computing
Volume27
Issue number8
DOIs
Publication statusPublished - 2 Jul 2009
Externally publishedYes

Keywords

  • Block matching
  • Local correlation
  • Print inspection
  • Separation of print layers

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