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Novelty detection of foreign objects in food using multi-modal X-ray imaging

Einarsdóttir, Hildur; Emerson, Monica Jane; Clemmensen, Line Harder; Scherer, Kai; Willer, Konstantin; Bech, Martin LU ; Larsen, Rasmus; Ersbøll, Bjarne Kjær and Pfeiffer, Franz (2016) In Food Control 67. p.39-47
Abstract

In this paper we demonstrate a method for novelty detection of foreign objects in food products using grating-based multimodal X-ray imaging. With this imaging technique three modalities are available with pixel correspondence, enhancing organic materials such as wood chips, insects and soft plastics not detectable by conventional X-ray absorption radiography. We conduct experiments, where several food products are imaged with common foreign objects typically found in the food processing industry. To evaluate the benefit from using this multi-contrast X-ray technique over conventional X-ray absorption imaging, a novelty detection scheme based on well known image- and statistical analysis techniques is proposed. The results show that the... (More)

In this paper we demonstrate a method for novelty detection of foreign objects in food products using grating-based multimodal X-ray imaging. With this imaging technique three modalities are available with pixel correspondence, enhancing organic materials such as wood chips, insects and soft plastics not detectable by conventional X-ray absorption radiography. We conduct experiments, where several food products are imaged with common foreign objects typically found in the food processing industry. To evaluate the benefit from using this multi-contrast X-ray technique over conventional X-ray absorption imaging, a novelty detection scheme based on well known image- and statistical analysis techniques is proposed. The results show that the presented method gives superior recognition results and highlights the advantage of grating-based imaging.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Dark-field imaging, Foreign object detection, Novelty detection, Phase-contrast imaging, Texture analysis, X-ray radiography
in
Food Control
volume
67
pages
9 pages
publisher
Elsevier
external identifiers
  • scopus:84959333129
  • wos:000375163800006
ISSN
0956-7135
DOI
10.1016/j.foodcont.2016.02.023
language
English
LU publication?
yes
id
70884aeb-0600-4d29-9dc3-286ac8541104
date added to LUP
2016-04-11 10:54:08
date last changed
2017-06-25 04:49:53
@article{70884aeb-0600-4d29-9dc3-286ac8541104,
  abstract     = {<p>In this paper we demonstrate a method for novelty detection of foreign objects in food products using grating-based multimodal X-ray imaging. With this imaging technique three modalities are available with pixel correspondence, enhancing organic materials such as wood chips, insects and soft plastics not detectable by conventional X-ray absorption radiography. We conduct experiments, where several food products are imaged with common foreign objects typically found in the food processing industry. To evaluate the benefit from using this multi-contrast X-ray technique over conventional X-ray absorption imaging, a novelty detection scheme based on well known image- and statistical analysis techniques is proposed. The results show that the presented method gives superior recognition results and highlights the advantage of grating-based imaging.</p>},
  author       = {Einarsdóttir, Hildur and Emerson, Monica Jane and Clemmensen, Line Harder and Scherer, Kai and Willer, Konstantin and Bech, Martin and Larsen, Rasmus and Ersbøll, Bjarne Kjær and Pfeiffer, Franz},
  issn         = {0956-7135},
  keyword      = {Dark-field imaging,Foreign object detection,Novelty detection,Phase-contrast imaging,Texture analysis,X-ray radiography},
  language     = {eng},
  month        = {09},
  pages        = {39--47},
  publisher    = {Elsevier},
  series       = {Food Control},
  title        = {Novelty detection of foreign objects in food using multi-modal X-ray imaging},
  url          = {http://dx.doi.org/10.1016/j.foodcont.2016.02.023},
  volume       = {67},
  year         = {2016},
}