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Details for article 4 of 9 found articles
| Title: |
Automated Defect Inspection Systems by Pattern Recognition |
| Author: |
Mira Park Jesse S. Jin Sherlock L. Au Suhuai Luo Yue Cui |
| Appeared in: |
International journal of signal processing, image processing and pattern recognition |
| Paging: | Volume 2 (2009) nr. 2 pages 31-42 |
| Year: |
2009 |
| Contents: |
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. |
| Publisher: |
SERSC (provided by DOAJ) |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 4 of 9 found articles
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