Binocular Stereo Vision Measuring System Based on Structured Light Extraction Algorithm

Author(s):  
Lingli Zhao ◽  
Haicheng Xu ◽  
Junsheng Li ◽  
Qun Cai
2013 ◽  
Vol 397-400 ◽  
pp. 1453-1458 ◽  
Author(s):  
Yu Bao Liu ◽  
Bin Liu ◽  
Jun Yi Lin

It is a difficult task to get enough numbers of highly accurate control points for projector calibration in line structured light vision system. A new projector calibration method based on binocular stereo vision is proposed in this paper. Two cameras calibration can be done usingtraditional camera calibration method and they composed a binocular stereo vision. In projector calibration procedure, a planar template was located at several different positions in front of the stereo vision system. Two cameras captured the stripe images in each position simultaneously. Every center points of the laser stripe can be used as control points of the projector plane. The 3D coordinate of the stripe center points can be obtained through binocular stereo vision principle easily. So the light plane can be calculated quickly. Experiments were carried out and the result shows that the proposed method is flexible and stable.


2021 ◽  
Vol 10 (4) ◽  
pp. 234
Author(s):  
Jing Ding ◽  
Zhigang Yan ◽  
Xuchen We

To obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay triangulation and Otsu threshold segmentation, is presented to separate a moving target from a complex background, called the Otsu Delaunay HS (O-DHS) method. Additionally, a stereo matching algorithm based on deep matching and stereo vision is presented to obtain dense stereo matching points pairs, called stereo deep matching (S-DM). The stereo matching point pairs of the moving target were extracted with the moving target area and stereo deep matching point pairs, then the three dimensional coordinates of the points in the moving target area were reconstructed according to the principle of binocular vision’s parallel structure. Finally, the moving target was located by the centroid method. The experimental results showed that this method can better resist image noise and repeated texture, can effectively detect and separate moving targets, and can match stereo image points in repeated textured areas more accurately and stability. This method can effectively improve the effectiveness, accuracy and robustness of three-dimensional moving target coordinates.


Optik ◽  
2021 ◽  
pp. 166651
Author(s):  
Lianghui Li ◽  
Jiachen Wang ◽  
Shengli Yang ◽  
Hao Gong

2021 ◽  
Author(s):  
Qingsheng Mu ◽  
Jun Wei ◽  
Zhugang Yuan ◽  
Yuheng Yin

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