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Multi-resolution analysis for region of interest extraction in thermographic, nondestructive evaluation

Benhur Ortiz Jaramillo UGent, Hermes Alexander Fandino Toro, Hernan Darío Benitez Restrepo, Sergio Alejandro Orjuela Vargas UGent, German Castellanos Dominguez and Wilfried Philips UGent (2012) Proceedings of SPIE, the International Society for Optical Engineering. 8295.
abstract
Infrared Non-Destructive Testing (INDT) is known as an effective and rapid method for nondestructive inspection. It can detect a broad range of near-surface structuring flaws in metallic and composite components. Those flaws are modeled as a smooth contour centered at peaks of stored thermal energy, termed Regions of Interest (ROI). Dedicated methodologies must detect the presence of those ROIs. In this paper, we present a methodology for ROI extraction in INDT tasks. The methodology deals with the difficulties due to the non-uniform heating. The non-uniform heating affects low spatial/frequencies and hinders the detection of relevant points in the image. In this paper, a methodology for ROI extraction in INDT using multi-resolution analysis is proposed, which is robust to ROI low contrast and non-uniform heating. The former methodology includes local correlation, Gaussian scale analysis and local edge detection. In this methodology local correlation between image and Gaussian window provides interest points related to ROIs. We use a Gaussian window because thermal behavior is well modeled by Gaussian smooth contours. Also, the Gaussian scale is used to analyze details in the image using multi-resolution analysis avoiding low contrast, non-uniform heating and selection of the Gaussian window size. Finally, local edge detection is used to provide a good estimation of the boundaries in the ROI. Thus, we provide a methodology for ROI extraction based on multi-resolution analysis that is better or equal compared with the other dedicate algorithms proposed in the state of art.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
Gaussian scale decomposition, SEGMENTATION, infrared nondestructive testing, pulse infrared thermography, region of interest
in
Proceedings of SPIE, the International Society for Optical Engineering
Proc. SPIE Int. Soc. Opt. Eng.
editor
Karen O Egiazarian, Sos S Agaian, Atanas P Gotchev, John Recker and Guijin Wang
volume
8295
issue title
Image processing : algorithms and systems X; and Parallel processing for imaging applications II
article_number
82951J
pages
9 pages
publisher
SPIE
place of publication
Bellingham, WA, USA
conference name
Conference on Image Processing : Algorithms and Systems X and Parallel Processing for Imaging Applications II
conference location
Burlingame, CA, USA
conference start
2012-01-23
conference end
2012-01-25
Web of Science type
Proceedings Paper
Web of Science id
000302532700048
ISSN
0277-786X
ISBN
9780819489425
DOI
10.1117/12.912079
language
English
UGent publication?
yes
classification
P1
copyright statement
I have transferred the copyright for this publication to the publisher
id
2010305
handle
http://hdl.handle.net/1854/LU-2010305
date created
2012-01-31 18:33:37
date last changed
2013-10-22 11:05:01
@inproceedings{2010305,
  abstract     = {Infrared Non-Destructive Testing (INDT) is known as an effective and rapid method for nondestructive inspection. It can detect a broad range of near-surface structuring flaws in metallic and composite components. Those flaws are modeled as a smooth contour centered at peaks of stored thermal energy, termed Regions of Interest (ROI). Dedicated methodologies must detect the presence of those ROIs. In this paper, we present a methodology for ROI extraction in INDT tasks. The methodology deals with the difficulties due to the non-uniform heating. The non-uniform heating affects low spatial/frequencies and hinders the detection of relevant points in the image. In this paper, a methodology for ROI extraction in INDT using multi-resolution analysis is proposed, which is robust to ROI low contrast and non-uniform heating. The former methodology includes local correlation, Gaussian scale analysis and local edge detection. In this methodology local correlation between image and Gaussian window provides interest points related to ROIs. We use a Gaussian window because thermal behavior is well modeled by Gaussian smooth contours. Also, the Gaussian scale is used to analyze details in the image using multi-resolution analysis avoiding low contrast, non-uniform heating and selection of the Gaussian window size. Finally, local edge detection is used to provide a good estimation of the boundaries in the ROI. Thus, we provide a methodology for ROI extraction based on multi-resolution analysis that is better or equal compared with the other dedicate algorithms proposed in the state of art.},
  articleno    = {82951J},
  author       = {Ortiz Jaramillo, Benhur and Fandino Toro, Hermes Alexander  and Benitez Restrepo, Hernan Dar{\'i}o  and Orjuela Vargas, Sergio Alejandro and Castellanos Dominguez, German  and Philips, Wilfried},
  booktitle    = {Proceedings of SPIE, the International Society for Optical Engineering},
  editor       = {Egiazarian, Karen O and Agaian, Sos S and Gotchev, Atanas P and Recker, John and Wang, Guijin},
  isbn         = {9780819489425},
  issn         = {0277-786X},
  keyword      = {Gaussian scale decomposition,SEGMENTATION,infrared nondestructive testing,pulse infrared thermography,region of interest},
  language     = {eng},
  location     = {Burlingame, CA, USA},
  pages        = {9},
  publisher    = {SPIE},
  title        = {Multi-resolution analysis for region of interest extraction in thermographic, nondestructive evaluation},
  url          = {http://dx.doi.org/10.1117/12.912079},
  volume       = {8295},
  year         = {2012},
}

Chicago
Ortiz Jaramillo, Benhur, Hermes Alexander Fandino Toro, Hernan Darío Benitez Restrepo, Sergio Alejandro Orjuela Vargas, German Castellanos Dominguez, and Wilfried Philips. 2012. “Multi-resolution Analysis for Region of Interest Extraction in Thermographic, Nondestructive Evaluation.” In Proceedings of SPIE, the International Society for Optical Engineering, ed. Karen O Egiazarian, Sos S Agaian, Atanas P Gotchev, John Recker, and Guijin Wang. Vol. 8295. Bellingham, WA, USA: SPIE.
APA
Ortiz Jaramillo, B., Fandino Toro, H. A., Benitez Restrepo, H. D., Orjuela Vargas, S. A., Castellanos Dominguez, G., & Philips, W. (2012). Multi-resolution analysis for region of interest extraction in thermographic, nondestructive evaluation. In K. O. Egiazarian, S. S. Agaian, A. P. Gotchev, J. Recker, & G. Wang (Eds.), Proceedings of SPIE, the International Society for Optical Engineering (Vol. 8295). Presented at the Conference on Image Processing : Algorithms and Systems X and Parallel Processing for Imaging Applications II, Bellingham, WA, USA: SPIE.
Vancouver
1.
Ortiz Jaramillo B, Fandino Toro HA, Benitez Restrepo HD, Orjuela Vargas SA, Castellanos Dominguez G, Philips W. Multi-resolution analysis for region of interest extraction in thermographic, nondestructive evaluation. In: Egiazarian KO, Agaian SS, Gotchev AP, Recker J, Wang G, editors. Proceedings of SPIE, the International Society for Optical Engineering. Bellingham, WA, USA: SPIE; 2012.
MLA
Ortiz Jaramillo, Benhur, Hermes Alexander Fandino Toro, Hernan Darío Benitez Restrepo, et al. “Multi-resolution Analysis for Region of Interest Extraction in Thermographic, Nondestructive Evaluation.” Proceedings of SPIE, the International Society for Optical Engineering. Ed. Karen O Egiazarian et al. Vol. 8295. Bellingham, WA, USA: SPIE, 2012. Print.