## 5 Discussion  
This paper proposes a novel system combining a camera and laser rangefinder for non-contact measurements from a long distance and adopts the combination of the improved U-net segmentation algorithm and Canny edge detection method to accurately measure the crack width of the concrete structure. This approach is very effective for solving crack measurement problems under non-contact conditions. Compared with traditional vertical photographing methods or other non-contact computer vision measurement research using a laser rangefinder [41], the proposed system considers the influence of pixel distortion caused by non-vertical photographing and calculates the unit pixel length of the image captured at any angle. Similar to the previous research, the photographing distance is measured by a laser rangefinder, but the error is corrected by parameters to make the results more accurate. This system adopts computer vision but without large machines [42], making it convenient for practical application. Moreover, in terms of the crack extraction algorithm, the method proposed in this paper also makes improvements. For the problem of data imbalance caused by the low crack pixel proportion in the image, an improved U-net algorithm is proposed by referring to the previous research and achieves good performance in the dataset [11; 17]. In addition, the Canny algorithm is introduced to refine the extracted crack edge to improve the measurement accuracy. Regarding the measurement results, the system proposed in this paper can not only realize measurement at a longer distance but also takes into account the influence of the photographing angle. The width of the measured crack is larger and the accuracy is higher compared with the previous research [28; 29; 43]. However, the proposed system has some limitations for the measurement of special cracks. Given that the cracks of large concrete structures are usually deep, some protrusions often occur deep in the cracks, as shown in Figure 27, which have the greatest impact on the crack extraction accuracy--Figure 27c is the crack in Figure 26f, and Figure 27d is the crack in Figure 26b. The segmentation algorithm usually emphasizes the color and shape of the crack, and because the changes in the depth of the cracks will make the edges blurred, some cracks may thus be unidentified. Therefore, for the images of the cracks  
\begin{table}
\begin{tabular}{l l l l l l l l} \hline \hline \multirow{2}{*}{**Image and Crack No. **} & \multirow{2}{*}{**Standard (mm)**} & \multicolumn{2}{l}{**Parameters**} & \multicolumn{3}{l}{**Crack Width and Error**} \\ \cline{3-8}  & & **Distance \(U\) (m)** & **Horizontal \(\theta_{b}\)** & **Vertical \(\theta_{v}\)** & **Measured (mm)** & **Error (mm)** & **Relative Value** \\ \hline (a)-1 & 6.27 & & & & 6.043 & 0.227 & 3.62\% \\ (a)-2 & 1.34 & 5.645 & 6\({}^{\circ}\) & 7\({}^{\circ}\) & 1.400 & \(-\)0.06 & \(-\)4.48\% \\ (a)-3 & 5.98 & & & &  
that occur in the concrete dam or other complex environment, more data covering the complex background and more patterns of cracks should be considered to improve U-net's capability of differentiating cracks on concrete building walls [16]. Compared with other measurement methods, such as Structure from Motion, the proposed approach is precise and convenient because it only requires one photograph without measured control points to achieve accurate non-contact measurement. Although the measurement system proposed in this study is not automated, it provides a computational method for long-distance, non-vertical measurement, and an automated system that requires hardware upgrades will be researched in the future. For long-term monitoring, the system has a broad application, and it is recommended to test this method on cheap cameras fixed on a structure in the future. To realize automatic measurement in the future, the measurement process of the laser measuring instrument should be simplified and triggered simultaneously with the camera to measure cracks in a single operation.