Paper Info
Title
Semi-automatic identification of print layers from a sequence of sample images: A case study from banknote print inspection
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.
Year
DOI
Venue
2009
10.1016/j.imavis.2008.08.008
Image Vision Comput.
Keywords
Field
DocType
separation of print layers,particular case study,print inspection process,banknote print inspection,image pair comparison,block matching,semi-automatic identification,sample images semi-automatically,local correlation,basic idea,sample image,print inspection,print layer,inspection system,paired comparison
Computer vision,Pattern recognition,Banknote,Test case,Pixel,Artificial intelligence,Mathematics
Journal
Volume
Issue
ISSN
27
8
Image and Vision Computing
Citations 
PageRank 
References 
0
0.34
15
Authors
4
Name
Order
Citations
PageRank
Daniel Soukup181.00
Ulrich Bodenhofer270568.02
Markus Mittendorfer-Holzer300.34
Konrad Mayer4453.34