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Texture wear analysis in textile floor coverings by using depth information

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Abstract
Considerable industrial and academic interest is addressed to automate the quality inspection of textile floor coverings, mostly using intensity images. Recently, the use of depth information has been explored to better capture the 3D structure of the surface. In this paper, we present a comparison of features extracted from three texture analysis techniques. The evaluation is based on how well the algorithms allow a good linear ranking and a good discriminance of consecutive wear labels. The results show that the use of Local Binary Patterns techniques result in a better ranking of the wear labels as well as in a higher amount of discrimination between features related to consecutive degrees of wear.
Keywords
Automated quality assessment, Image analysis, texture analysis, Wear analysis, texture feature extraction

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Chicago
Orjuela Vargas, Sergio Alejandro, Ewout Vansteenkiste, Filip Rooms, Simon De Meulemeester, Robain De Keyser, and Wilfried Philips. 2010. “Texture Wear Analysis in Textile Floor Coverings by Using Depth Information.” In XV Simposio De Tratamiento De Señales, Imágenes y Visión Artificial : STSIVA 2010, 101–106. Bogotá, Colombia: Escuela Colombiana de Ingeniería. STSIVA.
APA
Orjuela Vargas, S. A., Vansteenkiste, E., Rooms, F., De Meulemeester, S., De Keyser, R., & Philips, W. (2010). Texture wear analysis in textile floor coverings by using depth information. XV Simposio de Tratamiento de Señales, Imágenes y Visión Artificial : STSIVA 2010 (pp. 101–106). Presented at the XV Simposio de Tratamiento de Señales, Imágenes y Visión Artificial (STSIVA 2010), Bogotá, Colombia: Escuela Colombiana de Ingeniería. STSIVA.
Vancouver
1.
Orjuela Vargas SA, Vansteenkiste E, Rooms F, De Meulemeester S, De Keyser R, Philips W. Texture wear analysis in textile floor coverings by using depth information. XV Simposio de Tratamiento de Señales, Imágenes y Visión Artificial : STSIVA 2010. Bogotá, Colombia: Escuela Colombiana de Ingeniería. STSIVA; 2010. p. 101–6.
MLA
Orjuela Vargas, Sergio Alejandro, Ewout Vansteenkiste, Filip Rooms, et al. “Texture Wear Analysis in Textile Floor Coverings by Using Depth Information.” XV Simposio De Tratamiento De Señales, Imágenes y Visión Artificial : STSIVA 2010. Bogotá, Colombia: Escuela Colombiana de Ingeniería. STSIVA, 2010. 101–106. Print.
@inproceedings{1060898,
  abstract     = {Considerable industrial and academic interest is addressed to automate the quality inspection of textile floor coverings, mostly using intensity images. Recently, the use of depth information has been explored to better capture the 3D structure of the surface. In this paper, we present a comparison of features extracted from three texture analysis techniques. The evaluation is based on how well the algorithms allow a good linear ranking and a good discriminance of consecutive wear labels. The results show that the use of Local Binary Patterns techniques result in a better ranking of the wear labels as well as in a higher amount of discrimination between features related to consecutive degrees of wear.},
  articleno    = {36},
  author       = {Orjuela Vargas, Sergio Alejandro and Vansteenkiste, Ewout and Rooms, Filip and De Meulemeester, Simon and De Keyser, Robain and Philips, Wilfried},
  booktitle    = {XV Simposio de Tratamiento de Se{\~n}ales, Im{\'a}genes y Visi{\'o}n Artificial : STSIVA 2010},
  isbn         = {9789588060965},
  keyword      = {Automated quality assessment,Image analysis,texture analysis,Wear analysis,texture feature extraction},
  language     = {eng},
  location     = {Bogot{\'a}, Colombia},
  pages        = {36:101--36:106},
  publisher    = {Escuela Colombiana de Ingenier{\'i}a. STSIVA},
  title        = {Texture wear analysis in textile floor coverings by using depth information},
  year         = {2010},
}