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- Pahlberg, TobiasLuleå tekniska universitet,Träteknik,Luleå University of Technology, Campus Skellefteå, Skellefteå, Sweden (author)
Crack detection in oak flooring lamellae using ultrasound-excited thermography
- Article/chapterEnglish2018
Publisher, publication year, extent ...
- Elsevier,2018
- printrdacarrier
Numbers
- LIBRIS-ID:oai:DiVA.org:hj-38305
- https://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-38305URI
- https://doi.org/10.1016/j.infrared.2017.11.007DOI
- https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-65698URI
Supplementary language notes
- Language:English
- Summary in:English
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Notes
- Validerad;2017;Nivå 2;2017-12-05 (andbra)
- 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 and genre
- 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
- 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
Added entries (persons, corporate bodies, meetings, titles ...)
- Thurley, MatthewLuleå tekniska universitet,Signaler och system,Luleå University of Technology, Luleå, Sweden(Swepub:ltu)mjt (author)
- Popovic, Djordje,1985-Jönköping University,JTH, Logistik och verksamhetsledning,JTH, Industriell produktutveckling, produktion och design(Swepub:hj)popdjo (author)
- Hagman, Olle,1956-Luleå tekniska universitet,Träteknik,Luleå University of Technology, Campus Skellefteå, Skellefteå, Sweden(Swepub:ltu)ollhag (author)
- Luleå tekniska universitetTräteknik (creator_code:org_t)
Related titles
- In:Infrared physics & technology: Elsevier88, s. 57-691350-44951879-0275
Internet link
- http://ltu.diva-portal.org/smash/get/diva2:1142016/FULLTEXT01
- https://ltu.diva-portal.org/smash/get/diva2:1142016/FULLTEXT01.pdffulltext:postprint
- https://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-38305
- https://doi.org/10.1016/j.infrared.2017.11.007
- https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-65698
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