Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A computer vision system for appearance-based descriptive sensory evaluation of meals
RISE, SP – Sveriges Tekniska Forskningsinstitut, SP Sveriges tekniska forskningsinstitut, SIK – Institutet för livsmedel och bioteknik.
2007 (English)In: Journal of Food Engineering, ISSN 0260-8774, E-ISSN 1873-5770, Vol. 78, no 1, p. 246-256Article in journal (Refereed)
Abstract [en]

This paper presents a complete machine vision system for automatic descriptive sensory evaluation of meals. A human sensory panel first developed a set of 72 sensory attributes describing the appearance of a prototypical meal, and then evaluated the intensities of those attributes on a data set of 58 images of example meals. This data was then used both to train and validate the performance of the artificial system. This system covers all stages of image analysis from pre-processing to pattern recognition, including novel techniques for enhancing the segmentation of meal components and extracting image features that mimic the attributes developed by the panel. Artificial neural networks were used to learn the mapping from image features to attribute intensity values. The results showed that the new system was extremely good in learning and reproducing the opinion of the human sensory experts, achieving almost the same performance as the panel members themselves. © 2005 Elsevier Ltd. All rights reserved.

Place, publisher, year, edition, pages
2007. Vol. 78, no 1, p. 246-256
Keywords [en]
Food Engineering
Keywords [sv]
Livsmedelsteknik
National Category
Food Science
Identifiers
URN: urn:nbn:se:ri:diva-8887DOI: 10.1016/j.jfoodeng.2005.09.033OAI: oai:DiVA.org:ri-8887DiVA, id: diva2:966760
Available from: 2016-09-08 Created: 2016-09-08 Last updated: 2020-12-01Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full texthttp://www.scopus.com/inward/record.url?eid=2-s2.0-33745935352&partnerID=40&md5=a91d142c3954bb0d355f4b9b0f689993
By organisation
SIK – Institutet för livsmedel och bioteknik
In the same journal
Journal of Food Engineering
Food Science

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 33 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf