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Automated Defect Inspection Systems by Pattern Recognition

Author(s): Mira Park | Jesse S. Jin | Sherlock L. Au | Suhuai Luo | Yue Cui

Journal: International Journal of Signal Processing, Image Processing and Pattern Recognition
ISSN 2005-4254

Volume: 2;
Issue: 2;
Start page: 31;
Date: 2009;
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Keywords: Pattern Recognition | Automated Defect Inspection Systems | Cigarette

Visual inspection and classification of cigarettes packaged in a tin container is very important in manufacturing cigarette products that require high quality package presentation. For accurate automated inspection and classification, computer vision has been deployed widely in manufacturing. We present the detection of the defective packaging of tins of cigarettes by identifying individual objects in the cigarette tins. Object identification information is used for the classification of the acceptable cases (correctly packaged tins) or defective cases (incorrectly packaged tins). This paper investigates the problem of identifying the individual cigarettes and a paper spoon in the packaged tin using image processing andmorphology operations. The segmentation performance was evaluated on 500 images including examples of both good cases and defective cases.
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