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Metal component surfaces are random textured and non-smooth. There are many stains on the surface of metal component that are similar to the gray scale of the scratches. The scratches have non-uniform gray distribution, various shapes, and low contrast in their background, posing challenges in accurate scratch detection. This paper presents a method for detecting weak scratches on metal component surfaces based on deep convolutional neural networks (DCNNs). First, a DCNN is trained using labeled scratch images. Then, the scratches and some faults are detected by the trained DCNN, and most of the faults can be removed through properly thresholding based on the size of connected regions. Finally, the scratch length united in the number of pixels is obtained by the skeleton extraction. The experimental results show that the proposed method can effectively deal with background noise, thereby achieving accurate scratch detection.

This study summarizes and condenses the core requirements of green road construction in the reconstruction and expansion project, systematically analyzes the three typical representative green road evaluation index systems of GreenRoads, INVEST and Green-LITES. A green highway evaluation index system including 7 first-level indicators, 20 second-level indicators, and 52 third-level indicators has been constructed, The analytic hierarchy process was used to establish a step-level model, the relative importance of each index is determined according to the judgment of experts, and the weight coefficient of each level of index is obtained. In terms of policy requirements, related technology applications, green highway development trends, and the actual construction of the Beijing-Shanghai Expressway reconstruction and expansion project, the three-level indicator scoring method was determined. The green highway evaluation index system and evaluation model were used to evaluate the reconstruction and expansion project of the Beijing-Shanghai Expressway from Laiwu to Linyi (Lu-Sujie). It was determined that the comprehensive score of the project was 81.2, which reaching an excellent level.

The non-contact three-dimensional measurement and reconstruction techniques have played a significant role in the packaging and transportation of precious cultural relics. This paper develops a structured light based three-dimensional measurement system, with a low-cost for cultural relics packaging. The structured light based system performs rapid measurements and generates 3D point cloud data, which is then denoised, registered and merged to achieve accurate 3D reconstruction for cultural relics. The multi-frequency heterodyne method and the method in this paper are compared. It is shown that the relative accuracy of the proposed low-cost system can reach a level of 1/1000. The high efficiency of the system is demonstrated through experimental results.