KEYWORDS: Clouds, Denoising, Digital filtering, Signal to noise ratio, Image segmentation, Optical filters, Visualization, Data acquisition, Principal component analysis
The assembly gap between components is very vital for the evaluation of assembly quality of aircrafts. Due to the limits of gap size and operation space, the assembly gap needs to be indirectly calculated by the measurements of surface of components instead of plug gauge test. However, the surface constituted of point cloud is usually mixed with different types of noise ,which severely affects the evaluation of assembly gap. To remove these different types of noise simultaneously with high efficiency, a classified denoising method combining with an improved bilateral filtering and median filtering was proposed. Firstly, based on the principal component analysis, a new coordinate system was established to achieve the homogeneity of coordinates of point cloud. Then, an improved median filtering method on the basis of region segmentation (RSMF) was used to remove large-scale noise. Next, the fast bilateral filtering method based on threshold segmentation (TSBF) was proposed to remove small-scale noise. Finally, a measurement experiment of aircraft component was performed to verify the effectiveness of the proposed method. Experimental results showed that the proposed method could not only reduce measurement error including RMSE (Root Mean Square Error), but also improve SNR (Signal Noise Ratio) and PSNR (Peak Signal to Noise Ratio) of point cloud data.
KEYWORDS: Cameras, Distortion, Calibration, 3D modeling, Visual process modeling, Imaging systems, 3D image processing, 3D metrology, 3D acquisition, Cesium
The traditional vision measurement model has difficulty in guaranteeing the accuracy of measurement in the depth of field. And in this way, high-precision measurement of large components parts in three-dimensional large scale space can hardly be realized. To solve this problem, a binocular measuring method based on 3D image distortion compensation is proposed. Considering the rule of image distortion in the three-dimensional space, and combining with binocular vision measurement principle, a new binocular vision measurement model, based on 3D image distortion compensation, is established in the paper. And the model is based on the rule of image distortion in the three-dimensional space, and combined with binocular vision measurement principle. Besides, a new calibration method is proposed. This method is for the distortion parameters of the model and the intrinsic parameters of the cameras. Experimental results show that the proposed binocular vision measurement method in this paper is much more effectively than the traditional method. The results indicate that the proposed method largely improves the measurement accuracy under the condition of large depth of field. Meanwhile, this method also significantly improves the measurement accuracy in the three-dimensional space.
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