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논문검색

Automated Defect Inspection Systems by Pattern Recognition

초록

영어

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 and morphology operations. The segmentation performance was evaluated on 500 images including examples of both good cases and defective cases.

목차

Abstract
 1. Introduction
 2. Methods
  2.1. Counting objects in an image
  2.2. Paper “spoon” handle identification
 3. Experimental Results
 4. Conclusions
 References

저자정보

  • Mira Park The School of Design, Communication & IT, The University of Newcastle, Australia
  • Jesse S. Jin The School of Design, Communication & IT, The University of Newcastle, Australia
  • Sherlock L. Au Multi Base Ltd, Hong Kong
  • Suhuai Luo The School of Design, Communication & IT, The University of Newcastle, Australia
  • Yue Cui The School of Design, Communication & IT, The University of Newcastle, Australia

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