To improve the three-dimensional (3D) reconstruction effect of intelligent manufacturing image and reduce the reconstruction time, a new CAD-aided 3D reconstruction of intelligent manufacturing image based on time series was proposed. Kinect sensor is used to collect depth image data and convert it into 3D point cloud coordinates. The collected point cloud data are divided into regions, and different point cloud denoising algorithms are used to filter and denoise the divided regions. With the help of CAD, FLANN matching algorithm is used to extract feature points of time-series images and complete image matching. Three-dimensional reconstruction of sparse point cloud and dense point cloud is carried out to complete 3D reconstruction of intelligent manufacturing images. The experimental results show that the image PSNR of this method is always above 52 dB, and the maximum reconstruction time is 4.9 s. The 3D reconstruction effect of intelligent manufacturing image is better, and it has higher practical application value.
CITATION STYLE
Zhang, L., Wang, L., Du, X., & Meng, F. (2022). CAD-Aided 3D Reconstruction of Intelligent Manufacturing Image Based on Time Series. Scientific Programming, 2022. https://doi.org/10.1155/2022/9022563
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