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In order to realize the rapid detection of three-dimensional defects of connectors, this paper proposes a method for detecting connector defects based on structured light. This method combines structured light with binocular stereo vision to obtain three-dimensional data for the connector. Point cloud registration is used to identify defects and decision trees are used to classify defects. The accuracy of the 3D reconstruction results in this paper is 0.01 mm, the registration accuracy of the point cloud reaches the sub-millimeter level, and the final defect classification accuracy is 94%. The experimental results prove the effectiveness of the proposed three-dimensional connector defect detection method in connector defect detection and classification.

To quickly obtain accurate 3D data of dental cast model, this paper proposes a 3D reconstruction method for dental cast model based on structured light. This method combines the structured light with the motor turntable to obtain a group of 3D data for the dental cast model from multiple angles, and automatically registers the dental 3D data from multiple angles through the ball calibration of turntable. Compared with the real data of the dental cast model, the maximum error of the 3D reconstruction results in this paper is 0.115 mm. The reconstruction time of this process is about 130 s. The experimental results show that the method has high precision and high scanning speed for the 3D reconstruction of the dental cast model.

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.