Measurement of knot width in CT images of Norway spruce (Picea abies [L.] Karst.)—Evaluating the accuracy of an image analysis method

X-ray computed tomography (CT) is an effective scanning technology for imaging inner roundwood features. It is assumed that using this technology for log inspection prior to the first conversion could further optimise raw material utilisation. If the information obtained by CT scanning of a log shall be exploited in an industrial application, automated interpretation of CT images is a necessity. An image analysis method for knot extraction and measurement was tested on CT images of Norway spruce (Picea abies L.] Karst.) produced by a prototype of a dedicated roundwood CT scanner. Measurement accuracy was evaluated through a comparison of the computer measurements obtained on single CT slices to reference measurements obtained manually on physical log cross-sections that corresponded to the images treated. In a linear regression established from 119 measurement pairs 68% of the variation of the manually measured knot width could be explained by the variation of the computer measurements. Bias and root mean squared error (RMSE) were 1.7 mm and 4 mm, respectively. Hence the measurements were generally in accordance, but an overestimation of knot width by the computer vision method was observed. An algorithm for removing bright sapwood areas from the CT images—necessary as a preparation for knot segmentation—has been found to fail at images of logs with partly dried sapwood; this problem was identified as the primary reason for the loss of 28% of the measurements originally to be acquired and for the occurrence of erroneous measurements. It should be investigated whether a modification of this algorithm could enhance the performance and accuracy of the method.