Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/802625
- Title
- Pattern recognition from segmented images in automated inspection systems
- Author/Creator
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Park, Mira;
Jin, Jesse S.;
Au, Sherlock L.;
Luo, Suhuai
- Institution
- The University of Newcastle. Faculty of Science & Information Technology, School of Design, Communication and Information Technology
- Description
- We present the segmentation of the foreground objects and the identification of the individual objects in the cigarette tin package, so the information will be used for the classification of the acceptable cases or defective cases. Visual inspection and classification of cigarette tin package are very important in manufacturing cigarette products that require high quality package. For the accurate automated inspection and classification, computer vision has been deployed widely in manufacturing. This paper concerned with the problem of identifying the individual cigarette in the tin packing using the image processing and morphology operations. The identified objects can be used for developing a defect finding system in the cigarette packing industries. The approach has two steps: (i) colour-based segmentation of the region of interests, (ii) identifying of individual object. The segmentation performance was evaluated on 18 images including the good cases and the defective cases.
- Relation
- International Symposium on Ubiquitous Multimedia Computing (UMC-08). Proceedings: 2008 International Symposium on Ubiquitous Multimedia Computing, UMC 2008 (Hobart, Tas. 13-15 October, 2008) p. 87-92
- Publisher Link
- http://dx.doi.org/10.1109/UMC.2008.26
- Date
- 2008
- Publisher
- IEEE Computer Society
- Keyword(s)
-
automated inspection systems;
pattern recognition
- Resource Type
- conference paper
- Rights
- Copyright © 2008 IEEE. Reprinted from the Proceedings: 2008 International Symposium on Ubiquitous Multimedia Computing, UMC 2008. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Newcastle's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
- Identifier
- http://hdl.handle.net/1959.13/802625
- Identifier
- ISBN:9780769534275
- Reviewed
- Full Text
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