Title :
Pattern Recognition from Segmented Images in Automated Inspection Systems
Author :
Park, Mira ; Jin, Jesse S. ; Au, Sherlock L. ; Luo, Suhuai
Author_Institution :
Sch. of Design, Commun. & IT, Univ. of Newcastle, Newcastle, NSW
Abstract :
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.
Keywords :
image classification; image colour analysis; image segmentation; inspection; mathematical morphology; packaging; production engineering computing; tobacco industry; tobacco products; automated inspection systems; case classification; cigarette packing industries; cigarette product manufacturing; cigarette tin package; colour-based segmentation; computer vision; defect finding system; image segmentation; morphology; pattern recognition; Computer aided manufacturing; Computer vision; Image processing; Image segmentation; Inspection; Manufacturing automation; Object recognition; Packaging; Pattern recognition; Tin; Automated Inspection Systems; Pattern Recognition;
Conference_Titel :
Ubiquitous Multimedia Computing, 2008. UMC '08. International Symposium on
Conference_Location :
Hobart, ACT
Print_ISBN :
978-0-7695-3427-5
DOI :
10.1109/UMC.2008.26