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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/927118
- Automated pattern recognition and defect inspection system
Jin, Jesse S.;
Au, Sherlock S. L.
- The University of Newcastle. Faculty of Science & Information Technology, School of Design Communication and Information Technology
- Packaging appearance is extremely important in cigarette manufacturing. Typically, there are two types of cigarette packaging defects: (1) cigarette laying defects such as incorrect cigarette numbers and irregular layout; (2) tin paper handle defects such as folded paper handles. In this paper, an automated vision-based defect inspection system is designed for cigarettes packaged in tin containers. The first type of defects is inspected by counting the number of cigarettes in a tin container. First k-means clustering is performed to segment cigarette regions. After noise filtering, valid cigarette regions are identified by estimating individual cigarette area using linear regression. The k clustering centers and area estimation function are learned off-line on training images. The second kind of defect is detected by checking the segmented paper handle region. Experimental results on 500 test images demonstrate the effectiveness of the proposed inspection system. The proposed method also contributes to the general detection and classification system such as identifying mitosis in early diagnosis of cervical cancer.
- 5th International Conference on Image and Graphics (ICIG 2009). Proceedings of the 5th International Conference on Image and Graphics, ICIG 2009 (Xi'an, China 20-23 September, 2009) p. 768-773
- Publisher Link
- IEEE Computer Society
area estimation function;
automated pattern recognition;
automated vision based defect inspection system;
cigarette laying defect;
cigarette packaging defect;
tin paper handle defect
- Resource Type
- conference paper
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