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Crack detection in oak flooring lamellae using ultrasound-excited thermography

Pahlberg, Tobias (author)
Luleå tekniska universitet,Träteknik,Luleå University of Technology, Campus Skellefteå, Skellefteå, Sweden
Thurley, Matthew (author)
Luleå tekniska universitet,Signaler och system,Luleå University of Technology, Luleå, Sweden
Popovic, Djordje, 1985- (author)
Jönköping University,JTH, Logistik och verksamhetsledning,JTH, Industriell produktutveckling, produktion och design
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Hagman, Olle, 1956- (author)
Luleå tekniska universitet,Träteknik,Luleå University of Technology, Campus Skellefteå, Skellefteå, Sweden
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 (creator_code:org_t)
Elsevier, 2018
2018
English.
In: Infrared physics & technology. - : Elsevier. - 1350-4495 .- 1879-0275. ; 88, s. 57-69
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Today, a large number of people are manually grading and detecting defects in wooden lamellae in the parquet flooring industry. This paper investigates the possibility of using the ensemble methods random forests and boosting to automatically detect cracks using ultrasound-excited thermography and a variety of predictor variables. When friction occurs in thin cracks, they become warm and thus visible to a thermographic camera. Several image processing techniques have been used to suppress the noise and enhance probable cracks in the images. The most successful predictor variables captured the upper part of the heat distribution, such as the maximum temperature, kurtosis and percentile values 92–100 of the edge pixels. The texture in the images was captured by Completed Local Binary Pattern histograms and cracks were also segmented by background suppression and thresholding. The classification accuracy was significantly improved from previous research through added image processing, introduction of more predictors, and by using automated machine learning. The best ensemble methods reach an average classification accuracy of 0.8, which is very close to the authors’ own manual attempt at separating the images (0.83).

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Materialteknik -- Metallurgi och metalliska material (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Materials Engineering -- Metallurgy and Metallic Materials (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Annan maskinteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Other Mechanical Engineering (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)

Keyword

Crack detection
Ensemble classification
Machine learning
Parquet flooring
Ultrasound-excited thermography
Wood
Artificial intelligence
Building materials
Cracks
Decision trees
Floors
Grading
Image enhancement
Image processing
Learning algorithms
Learning systems
Statistical methods
Thermography (imaging)
Ultrasonic applications
Background suppression
Classification accuracy
Image processing technique
Local binary patterns
Predictor variables
Thermographic cameras
Träteknik
Signalbehandling

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ref (subject category)
art (subject category)

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