Skip to Main Content
Using parallel computing methods to improve log surface defect detection methodsAuthor(s): R. Edward Thomas; Liya Thomas
Source: In: Ross, Robert J.; Wang, Xiping, eds. Proceedings, 18th International Nondestructive Testing and Evaluation of Wood Symposium; 2013 September 24-27; Madison, WI. Gen. Tech. Rep. FPL-226. Madison, WI: U.S. Department of Agriculture, Forest Service, Forest Products Laboratory: 196-205.
Publication Series: Paper (invited, offered, keynote)
Station: Northern Research Station
PDF: View PDF (752.78 KB)
Related Research Highlights
Improved Automated Detection of Surface Defects on Hardwood Logs
DescriptionDetermining the size and location of surface defects is crucial to evaluating the potential yield and value of hardwood logs. Recently a surface defect detection algorithm was developed using the Java language. This algorithm was developed around an earlier laser scanning system that had poor resolution along the length of the log (15 scan lines per foot). A newer laser scanning system was constructed that had much greater resolution (192 scan lines per foot) along the logs' length. The increased resolution and the slower processing speed of the Java-based algorithm required a new approach. The revised algorithm was designed around the higher resolution data and employs parallel processing technology. The new algorithm processes higher resolution data in less time than required by the original algorithm using the lower resolution scan data. The improved processing power permits a more in-depth analysis of the higher resolution scan data scan data leading to improved detection results.
- Check the Northern Research Station web site to request a printed copy of this publication.
- Our on-line publications are scanned and captured using Adobe Acrobat.
- During the capture process some typographical errors may occur.
- Please contact Sharon Hobrla, email@example.com if you notice any errors which make this publication unusable.
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationThomas, R. Edward; Thomas, Liya. 2013. Using parallel computing methods to improve log surface defect detection methods. In: Ross, Robert J.; Wang, Xiping, eds. Proceedings, 18th International Nondestructive Testing and Evaluation of Wood Symposium; 2013 September 24-27; Madison, WI. Gen. Tech. Rep. FPL-226. Madison, WI: U.S. Department of Agriculture, Forest Service, Forest Products Laboratory: 196-205.
Keywordshardwood, log, defect, automated detection, parallel processing
- Combining acoustic and laser scanning methods to improve hardwood log segregation
- Defect detection on hardwood logs using high resolution three-dimensional laser scan data
- Primary detection of hardwood log defects using laser surface scanning
XML: View XML