Automating Visual Inspection of Print Quality

• Published in: Image Analysis and Recognition pp. 877 - 885
• Main Authors: Vartiainen, J., Lyden, S., Sadovnikov, A., Kamarainen, J. -K., Lensu, L., Paalanen, P., Kalviainen, H.
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2006; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Applied sciences; Artificial intelligence; Computer science; control theory; systems; Exact sciences and technology; Machine Vision; Machine Vision System; Pattern recognition. Digital image processing. Computational geometry; Reciprocal Lattice; Reciprocal Lattice Point; Test Strip; Computer vision; Image analysis; Image recognition; Q factor; Image processing; Quality control; Counting; Visual control
• ISBN: 3540448942; 9783540448945; 3540448918; 9783540448914
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/11867661_79

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.