## 4 Experimental Results and Analysis
### Testing and Evaluation
For the cylinder, Figure 18a,b shows the captured images and 3D point measurement results of the cylinder. As shown in Figure 18a, the large error points are mainly distributed in the blackened parts of the cylinder and the edges of the cylinder. The stripe cross-sections intercepted in the irregular region and the regular region in Figure 18a are input into the prediction algorithm separately, and the results are shown in Figure 19. According to the prediction results in Figure 19a,b, both the points at the edge of the cylinder and the cross-sections of the structured light stripes in the blackened part are all severely defective. According to the prediction results in Figure 19c,d, the stripe cross-sections in the regions with more regular stripes have a uniform grayscale distribution and are evaluated as defect-free by the prediction algorithm. The stripe sections on the cylinder in Figure 18a are intercepted and input into the prediction algorithm separately. The points corresponding to the cross-sections with large errors evaluated by the algorithm are removed from the point cloud map shown in Figure 18b. The measurement error information before and after processing is shown in Table 9. The measurement error is defined as the absolute value of the difference between the distance from the point cloud on the cylinder to the fitted axis and the fitted radius of the cylinder. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Unprocessed** & \
\begin{tabular}{c} **Processed by the Method** \\ **in This Paper** \\ \end{tabular} &
\begin{tabular}{c} **Processed by the** \\ **Method in Ref. [19]** \\ \end{tabular} \\ \hline Mean/mm & 0.278 & 0.050 & 0.155 \\ Std/mm & 0.297 & 0.029 & 0.179 \\ Max/mm & 0.968 & 0.091 & 0.530 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Measurement Errors of the Flat Board. Figure 18: Measurement of the Cylinder. (**a**) Stripes on the Cylinder; (**b**) 3D Point Cloud of the Cylinder. As can be seen from Tables 7-9, the method proposed in this paper can accurately recognize the large error data. After removing the large error data, the maximum measurement error and the average measurement error of the stripes are reduced significantly. Compared with the method in Ref. [19], the average measurement error is lower after removing large error data using the method proposed in this paper. Since it does not need to calculate the evaluation parameters and set the thresholds of the parameters, it is much faster and more convenient. The comparison between the method proposed in this paper and the method proposed in Ref. [19] is shown in Table 10.  
Figure 19: Prediction Results of the Cylinder. (**a**) Prediction Results of Defective Cross-Sections at the Edges of the Cylinder; (**b**) Predicted Results of Defective Cross-Sections in Artificially Blackened Parts of Cylinders; (**c,d**) Prediction Results of Defect-Free Cross-Section. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Unprocessed** & \
\begin{tabular}{c} **Processed by the Method in** \\ **This Paper** \\ \end{tabular} &
\begin{tabular}{c} **Processed by the** \\ **Method in Ref. [19]** \\ \end{tabular} \\ \hline Mean/mm & 1.455 & 0.817 & 1.345 \\ Std/mm & 1.759 & 0.273 & 0.633 \\ Max/mm & 12.419 & 1.333 & 2.896 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Measurement Errors of the Cylinder.