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Erschienen in: Machine Vision and Applications 7/2016

01.10.2016 | Original Paper

Print registration for automated visual inspection of transparent pharmaceutical capsules

verfasst von: Andraž Mehle, Marko Bukovec, Boštjan Likar, Dejan Tomaževič

Erschienen in: Machine Vision and Applications | Ausgabe 7/2016

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Abstract

This paper addresses a challenging problem of visual inspection of transparent pharmaceutical capsules, where print registration is used to determine the capsule’s print region. The determination of the print region allows for reliable detection of defects both on the print region and on the rest of the capsule’s surface. On transparent capsules, both the print on the front and the print on the back of a capsule are concurrently visible. Moreover, the print on the back may be partially or entirely occluded by the powder inside the capsule. All this causes that the print registration methods used for opaque capsules do not achieve adequate performance. In this paper, we present a novel registration method designed specifically for transparent capsules. The method utilizes a template matching technique with a new similarity measure that considers the specific properties of transparent capsules to increase the registration robustness. Additionally, we present a registration refinement step that reduces the effect of possible print deformations and image distortions. The performance of the method was evaluated in terms of robustness, accuracy and speed on large image sets of four different radial prints. The new method shows highly improved robustness (>98.6 %) compared to the method based on normalized cross-correlation (>72 %) and the method based on feature matching (>80 %). Furthermore, the additional refinement step improves the registration accuracy. Although the execution time is raised from 3 to 11 ms, it still meets the usual speed requirements.

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Metadaten
Titel
Print registration for automated visual inspection of transparent pharmaceutical capsules
verfasst von
Andraž Mehle
Marko Bukovec
Boštjan Likar
Dejan Tomaževič
Publikationsdatum
01.10.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Machine Vision and Applications / Ausgabe 7/2016
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-016-0797-z

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