An explorative study on pork loin recognition

Anders Boesen Lindbo Larsen; Marchen Sonja Hviid; Rasmus Larsen; Anders Lindbjerg Dahl

An explorative study on pork loin recognition

Anders Boesen Lindbo Larsen, Marchen Sonja Hviid, Rasmus Larsen, Anders Lindbjerg Dahl

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

Bag-of-words (BoW) image description has shown good performance for a large variety of image recognition scenarios. We investigate approaches to alleviating a standard BoW image description pipeline representations for the specific task of recognizing pork loins. Specifically, we extend the BoW description to include depth maps, perform non-rigid image registration to align the images, and apply PCA dimensionality reduction on the BoW descriptors. Our results show that the combination of image registration and PCA yields a more distinctive recognition.

Original language	English
Title of host publication	Workshop on Farm Animal and Food Quality Imaging 2013 : Espoo, Finland, June 17, 2013, Proceedings
Place of Publication	Kgs. Lyngby
Publisher	Technical University of Denmark
Publication date	2013
Pages	49-54
Publication status	Published - 2013
Event	Workshop on Farm Animal and Food Quality Imaging 2013 - Espoo, Finland Duration: 17 Jun 2013 → 17 Jun 2013 http://www2.imm.dtu.dk/projects/WFAFQI/

Workshop

Workshop	Workshop on Farm Animal and Food Quality Imaging 2013
Country	Finland
City	Espoo
Period	17/06/2013 → 17/06/2013
Internet address	http://www2.imm.dtu.dk/projects/WFAFQI/

Series	DTU Compute-Technical Report-2013
Number	12
ISSN	1601-2321

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@inproceedings{7f589a28b27148aeaf4c28baabfd7885,

title = "An explorative study on pork loin recognition",

abstract = "Bag-of-words (BoW) image description has shown good performance for a large variety of image recognition scenarios. We investigate approaches to alleviating a standard BoW image description pipeline representations for the specific task of recognizing pork loins. Specifically, we extend the BoW description to include depth maps, perform non-rigid image registration to align the images, and apply PCA dimensionality reduction on the BoW descriptors. Our results show that the combination of image registration and PCA yields a more distinctive recognition.",

author = "Larsen, {Anders Boesen Lindbo} and Hviid, {Marchen Sonja} and Rasmus Larsen and Dahl, {Anders Lindbjerg}",

year = "2013",

language = "English",

series = "DTU Compute-Technical Report-2013",

publisher = "Technical University of Denmark",

number = "12",

pages = "49--54",

booktitle = "Workshop on Farm Animal and Food Quality Imaging 2013",

note = "Workshop on Farm Animal and Food Quality Imaging 2013, WFAFQI ; Conference date: 17-06-2013 Through 17-06-2013",

url = "http://www2.imm.dtu.dk/projects/WFAFQI/",

}

Larsen, ABL, Hviid, MS, Larsen, R & Dahl, AL 2013, An explorative study on pork loin recognition. in Workshop on Farm Animal and Food Quality Imaging 2013: Espoo, Finland, June 17, 2013, Proceedings. Technical University of Denmark, Kgs. Lyngby, DTU Compute-Technical Report-2013, no. 12, pp. 49-54, Workshop on Farm Animal and Food Quality Imaging 2013, Espoo, Finland, 17/06/2013.

An explorative study on pork loin recognition. / Larsen, Anders Boesen Lindbo; Hviid, Marchen Sonja; Larsen, Rasmus; Dahl, Anders Lindbjerg.

Workshop on Farm Animal and Food Quality Imaging 2013: Espoo, Finland, June 17, 2013, Proceedings. Kgs. Lyngby : Technical University of Denmark, 2013. p. 49-54 (DTU Compute-Technical Report-2013; No. 12).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AU - Hviid, Marchen Sonja

AU - Larsen, Rasmus

AU - Dahl, Anders Lindbjerg

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N2 - Bag-of-words (BoW) image description has shown good performance for a large variety of image recognition scenarios. We investigate approaches to alleviating a standard BoW image description pipeline representations for the specific task of recognizing pork loins. Specifically, we extend the BoW description to include depth maps, perform non-rigid image registration to align the images, and apply PCA dimensionality reduction on the BoW descriptors. Our results show that the combination of image registration and PCA yields a more distinctive recognition.

AB - Bag-of-words (BoW) image description has shown good performance for a large variety of image recognition scenarios. We investigate approaches to alleviating a standard BoW image description pipeline representations for the specific task of recognizing pork loins. Specifically, we extend the BoW description to include depth maps, perform non-rigid image registration to align the images, and apply PCA dimensionality reduction on the BoW descriptors. Our results show that the combination of image registration and PCA yields a more distinctive recognition.

M3 - Article in proceedings

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BT - Workshop on Farm Animal and Food Quality Imaging 2013

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