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Automated wear label assessment in carpets by using local binary pattern statistics on depth and intensity images

Sergio Alejandro Orjuela Vargas UGent, Filip Rooms UGent, Simon De Meulemeester, Robain De Keyser UGent and Wilfried Philips UGent (2010) Proceedings of the 2010 IEEE ANDESCON.
abstract
Carpet customers want a product of which the appearance lasts for years. Therefore, carpet manufacturers certify their products with labels that represent the expected change in appearance after the first year of installation. No automated system exists yet for objectively assigning these ranks. In this approach, we present an automated method for assessing carpet wear based on image analysis. For this, depth and intensity information are captured from eight types of carpet samples. The results show that the method correctly assigns wear labels from 1 to 5 in steps of 1 for six of the eight carpet types.
Please use this url to cite or link to this publication:
author
organization
year
type
conference (conferencePaper)
publication status
published
subject
keyword
Carpet Wear, Linear Models, Classification, Local Binay Patterns
in
Proceedings of the 2010 IEEE ANDESCON
article number
224
pages
5 pages
publisher
IEEE
place of publication
New York, NY, USA
conference name
IEEE Andescon & Latincom 2010 : Green technologies for a better world
conference location
Bogotá, Colombia
conference start
2010-09-14
conference end
2010-09-17
Web of Science type
Conference Paper
Web of Science id
11649483
ISBN
9781424467426
9781424467402
DOI
10.1109/ANDESCON.2010.5632443
language
English
UGent publication?
yes
classification
C1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1062689
handle
http://hdl.handle.net/1854/LU-1062689
date created
2010-10-22 12:52:23
date last changed
2017-03-09 12:10:40
@inproceedings{1062689,
  abstract     = {Carpet customers want a product of which the appearance lasts for years. Therefore, carpet manufacturers certify their products with labels that represent the expected change in appearance after the first year of installation. No automated system exists yet for objectively assigning these ranks. In this approach, we present an automated method for assessing carpet wear based on image analysis. For this, depth and intensity information are captured from eight types of carpet samples. The results show that the method correctly assigns wear labels from 1 to 5 in steps of 1 for six of the eight carpet types.},
  articleno    = {224},
  author       = {Orjuela Vargas, Sergio Alejandro and Rooms, Filip and De Meulemeester, Simon and De Keyser, Robain and Philips, Wilfried},
  booktitle    = {Proceedings of the 2010 IEEE ANDESCON},
  isbn         = {9781424467426},
  keyword      = {Carpet Wear,Linear Models,Classification,Local Binay Patterns},
  language     = {eng},
  location     = {Bogot{\'a}, Colombia},
  pages        = {5},
  publisher    = {IEEE},
  title        = {Automated wear label assessment in carpets by using local binary pattern statistics on depth and intensity images},
  url          = {http://dx.doi.org/10.1109/ANDESCON.2010.5632443},
  year         = {2010},
}

Chicago
Orjuela Vargas, Sergio Alejandro, Filip Rooms, Simon De Meulemeester, Robain De Keyser, and Wilfried Philips. 2010. “Automated Wear Label Assessment in Carpets by Using Local Binary Pattern Statistics on Depth and Intensity Images.” In Proceedings of the 2010 IEEE ANDESCON. New York, NY, USA: IEEE.
APA
Orjuela Vargas, S. A., Rooms, F., De Meulemeester, S., De Keyser, R., & Philips, W. (2010). Automated wear label assessment in carpets by using local binary pattern statistics on depth and intensity images. Proceedings of the 2010 IEEE ANDESCON. Presented at the IEEE Andescon & Latincom 2010 : Green technologies for a better world, New York, NY, USA: IEEE.
Vancouver
1.
Orjuela Vargas SA, Rooms F, De Meulemeester S, De Keyser R, Philips W. Automated wear label assessment in carpets by using local binary pattern statistics on depth and intensity images. Proceedings of the 2010 IEEE ANDESCON. New York, NY, USA: IEEE; 2010.
MLA
Orjuela Vargas, Sergio Alejandro, Filip Rooms, Simon De Meulemeester, et al. “Automated Wear Label Assessment in Carpets by Using Local Binary Pattern Statistics on Depth and Intensity Images.” Proceedings of the 2010 IEEE ANDESCON. New York, NY, USA: IEEE, 2010. Print.