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Effective inspector for detecting foreign substances in bottles with inhomogeneous structures

journal contribution
posted on 2018-02-16, 15:09 authored by Fangfang Yu, Rong Dong, Bo Li, Huiyu Zhou
In order to solve the problem of high costs and low efficiency caused by manual inspection, an automatic inspector for foreign substances in bottles with inhomogeneous structures based on machine vision technology is proposed in this paper. First, we extract the region of interest based on meanshift segmentation and align the images by registration and rectification. Then an adaptive image variation detection method is established to locate the potential foreign substances. To avoid the brightness disturbances caused by inhomogeneous structures on the bottles, an occurrence probability image which models the probability of each changed pixel to be true foreign substance is learned and candidate foreign substances are obtained by taking account of both the probability distribution and brightness variation. Finally, SVM classifier is applied to further identifying foreign substances based on their appearance features. Experiments show that this inspection algorithm has satisfactory detection accuracy and can greatly inhibit false detection caused by inhomogeneous structures.

Funding

This work is partially supported by the National Natural Science Foundation of China (Grant No.61401239) as well as Production and Research Project Foundation of Jiangsu Province (Grant No.BY2016075-01).

History

Citation

ICIC Express Letters, Part B: Applications, 2017, 8 (7), pp. 1031-1039

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/Organisation

Version

  • AM (Accepted Manuscript)

Published in

ICIC Express Letters

Publisher

ICIC International

issn

2185-2766

Copyright date

2017

Publisher version

http://www.icicelb.org/ellb/contents/2017/7/elb-08-07-03.pdf

Notes

The file associated with this record is under a permanent embargo in accordance with the publisher's policy. The full text may be available through the publisher links provided above.

Language

en

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