Abstract
Automatic evaluation of visual print quality is addressed in this study. Due to many complex factors of perceived visual quality its evaluation is divided to separate parts which can be individually evaluated using standardized assessments. Most of the assessments however require active evaluation by trained experts. In this paper one quality assessment, missing dot detection from printed dot patterns, is addressed by defining sufficient hardware for image acquisition and method for detecting and counting missing dots from a test strip. The experimental results are evidence how the human assessment can be automated with the help of machine vision, thus making the test more repeatable and accurate.
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© 2006 Springer-Verlag Berlin Heidelberg
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Vartiainen, J. et al. (2006). Automating Visual Inspection of Print Quality. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2006. Lecture Notes in Computer Science, vol 4142. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11867661_79
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DOI: https://doi.org/10.1007/11867661_79
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44894-5
Online ISBN: 978-3-540-44896-9
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