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Quality inspection of food packaging seals using machine vision with texture analysis

journal contribution
posted on 07.06.2006, 17:41 authored by David Kerr, Fangmin Shi, Neil Brown, Michael R. Jackson, Robert M. Parkin
This paper presents a machine vision approach to inspecting the integrity of semirigid polymer food packages sealed using a new laser-based sealing system. This new technique for food package sealing seeks to make significant improvements to existing manufacturing methods to meet the industry’s requirements for rapid response to retail customers, while maintaining high quality, through 100 per cent inspection, with low associated production costs. By analysing examples of ‘good’ and ‘bad’ seal images, seal uniformity has been examined and associated with numerical quality measures. Statistical texture analysis is utilized in order to distinguish between good and bad seal conditions. A minimum distance classifier and an artificial neural network have been used to accept the segmented texture parameters as inputs and to output the seal quality decision. The method is shown to have a high success rate provided that illumination conditions remain constant.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Pages

503523 bytes

Citation

KERR, D. ... et al, 2004. Quality inspection of food packaging seals using machine vision with texture analysis. Proceedings of I MECH E Part I Journal of Systems & Control Engineering, 219(3), pp. 321-237.

Publisher

© IMechE

Publication date

2004

Notes

This is Restricted Access. The article was published in the journal, Proceedings of the I Mech Eng Part I: Journal of Systems and Control Engineering, and is available at: http://journals.pepublishing.com/openurl.asp?genre=journal&issn=0959-6518.

ISSN

0959-6518

Language

es