DocumentCode :
2990542
Title :
Defect detection on hardwood logs using high resolution three-dimensional laser scan data
Author :
Thomas, Liya ; Mili, Lumine ; Shaffer, Clifford A. ; Thomas, Ed
Author_Institution :
Dept. of Comput. Sci., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
Volume :
1
fYear :
2004
fDate :
24-27 Oct. 2004
Firstpage :
243
Abstract :
The location, type, and severity of external defects on hardwood logs and stems are the primary indicators of overall log quality and value. External defects provide hints about the internal log characteristics. Defect data would improve the sawyer´s ability to process logs such that a higher valued product (lumber) is generated. Using a high-resolution laser log scanner, we scanned and digitally photographed 162 red-oak and yellow-poplar logs. By means of a new robust estimator that performs circle fitting, a residual image is extracted from laser scan data that are corrupted by extreme outliers induced by the scanning equipment and loose bark. The residuals provide information to identify defects with height differentiation from the log surface. Combining simple shape definition rules with the height map allows most severe defects to be detected by determining the contour levels of a residual image. In addition, bark texture changes can be examined such that defects not associated with a height change might be detected.
Keywords :
estimation theory; feature extraction; image texture; measurement by laser beam; regression analysis; shape measurement; surface topography; wood processing; bark texture changes; circle fitting; hardwood log defect detection; height map; high resolution 3D laser scan data; image contour levels; log external defects; log quality; log shape estimation; log surface height differentiation; lumber; nonlinear regression model; outliers; red-oak logs; residual image extraction; robust estimator; shape definition rules; wood processing; yellow-poplar logs; Computer science; Data mining; Laser theory; Robustness; Rough surfaces; Sawing; Shape; Springs; Surface fitting; US Department of Agriculture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2004. ICIP '04. 2004 International Conference on
ISSN :
1522-4880
Print_ISBN :
0-7803-8554-3
Type :
conf
DOI :
10.1109/ICIP.2004.1418735
Filename :
1418735
Link To Document :
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