Polarised light stress analysis and laser scatter imaging for non-contact inspection of heat seals in food trays

Barnes, Michael and Dudbridge, Michael and Duckett, Tom (2012) Polarised light stress analysis and laser scatter imaging for non-contact inspection of heat seals in food trays. Journal of Food Engineering, 112 (3). pp. 183-190. ISSN 0260-8774

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Polarised light stress analysis and laser scatter imaging for non-contact inspection of heat seals in food trays
(preprint submitted to Elsevier)
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Official URL: http://dx.doi.org/10.1016/j.jfoodeng.2012.02.040

Abstract

This paper introduces novel non-contact methods for detecting faults in heat seals of food packages. Two alternative imaging technologies are investigated; laser scatter imaging and polarised light stress images. After segmenting the seal area from the rest of the respective image, a classifier is trained to detect faults in different regions of the seal area using features extracted from the pixels in the respective region. A very large set of candidate features, based on statistical information relating to the colour and texture of each region, is first extracted. Then an adaptive boosting algorithm (AdaBoost) is used to automatically select the best features for discriminating faults from non-faults. With this approach, different features can be selected and optimised for the different imaging methods. In experiments we compare the performance of classifiers trained using features extracted from laser scatter images only, polarised light stress images only, and a combination of both image types. The results show that the polarised light and laser scatter classifiers achieved accuracies of 96\% and 90\%, respectively, while the combination of both sensors achieved an accuracy of 95\%. These figures suggest that both systems have potential for commercial development.

Item Type:Article
Keywords:Photoelasticity, Computer vision, Polarised light, Food engineering
Subjects:D Veterinary Sciences, Agriculture and related subjects > D610 Food Science
G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > National Centre for Food Manufacturing
College of Science > School of Computer Science
ID Code:5513
Deposited By: Michael Barnes
Deposited On:16 May 2012 09:00
Last Modified:04 Dec 2013 16:25

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