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Picture of Improved Automated Detection of Surface Defects on Hardwood Logs
NRS-2014-056
Improved Automated Detection of Surface Defects on Hardwood Logs

Title: Using parallel computing methods to improve log surface defect detection methods

Author: Thomas, R. Edward; Thomas, Liya.;

Date: 2013

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)

Description: Determining 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.

Keywords: hardwood, log, defect, automated detection, parallel processing

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Citation:


Thomas, 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.

 


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