scholarly journals Three-dimensional mechanical parts reconstruction technology based on two-dimensional image

2020 ◽  
Vol 17 (2) ◽  
pp. 172988142091000
Author(s):  
Jiaofei Huo ◽  
Xiaomo Yu
Keyword(s):  
Image Processing ◽  
Stereo Vision ◽  
Stereo Matching ◽  
Vision System ◽  
Three Dimensional ◽  
Three Dimensional Reconstruction ◽  
Stereo Vision System ◽  
Binocular Stereo Vision ◽  
Extraction Algorithm ◽  
Dimensional Reconstruction

With the development of computer technology and three-dimensional reconstruction technology, three-dimensional reconstruction based on visual images has become one of the research hotspots in computer graphics. Three-dimensional reconstruction based on visual image can be divided into three-dimensional reconstruction based on single photo and video. As an indirect three-dimensional modeling technology, this method is widely used in the fields of film and television production, cultural relics restoration, mechanical manufacturing, and medical health. This article studies and designs a stereo vision system based on two-dimensional image modeling technology. The system can be divided into image processing, camera calibration, stereo matching, three-dimensional point reconstruction, and model reconstruction. In the part of image processing, common image processing methods, feature point extraction algorithm, and edge extraction algorithm are studied. On this basis, interactive local corner extraction algorithm and interactive local edge detection algorithm are proposed. It is found that the Harris algorithm can effectively remove the features of less information and easy to generate clustering phenomenon. At the same time, the method of limit constraints is used to match the feature points extracted from the image. This method has high matching accuracy and short time. The experimental research has achieved good matching results. Using the platform of binocular stereo vision system, each step in the process of three-dimensional reconstruction has achieved high accuracy, thus achieving the three-dimensional reconstruction of the target object. Finally, based on the research of three-dimensional reconstruction of mechanical parts and the designed binocular stereo vision system platform, the experimental results of edge detection, camera calibration, stereo matching, and three-dimensional model reconstruction in the process of three-dimensional reconstruction are obtained, and the full text is summarized, analyzed, and prospected.

scholarly journals High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision

2021 ◽  
Vol 10 (4) ◽  
pp. 234
Author(s):  
Jing Ding ◽  
Zhigang Yan ◽  
Xuchen We
Keyword(s):  
Stereo Vision ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Target Localization ◽  
Parallel Structure ◽  
Moving Target ◽  
Target Area ◽  
Moving Targets ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

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.

<i>A Binocular Stereo Vision System of Fruits Picking Robots Based on Embedded System </i>

2020 ◽  
Author(s):  
Pengcheng Wang ◽  
Zenghong Ma ◽  
Xiaoqiang Du ◽  
Wenwu Lu ◽  
Wensong Xing ◽  
...  
Keyword(s):  
Embedded System ◽  
Stereo Vision ◽  
Vision System ◽  
Stereo Vision System ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

PRECISE SHAPE MEASUREMENT OF DYNAMIC SURFACE VIA SINGLE CAMERA STEREO

2006 ◽  
Vol 03 (01) ◽  
pp. 53-60
Author(s):  
LUPING AN ◽  
YUNDE JIA ◽  
MINGTAO PEI ◽  
HONGBIN DENG
Keyword(s):  
Stereo Vision ◽  
Stereo Matching ◽  
Vision System ◽  
Least Square ◽  
Shape Measurement ◽  
Single Camera ◽  
Dynamic Surface ◽  
Moving Least Square ◽  
Stereo Vision System ◽  
Precise Shape

In this article, a method of the precise shape measurement of dynamic surfaces via a single camera stereo vision system is presented, a cross-curve pattern is painted on the surface of an object, and the intersections of cross-curves which represent the shape of the object are measured by the stereo vision system. The system with a single camera is modeled as a virtual binocular stereo by strong calibration technique. Binocular epipolar rectification is used to make the stereo matching efficient, and principal curves theory is employed to extract curves in images for stereo matching. Under the framework of RANSAC, the curves are interpolated robustly with cubic spline based on moving-least-square (MLS). Experimental results on both static and dynamic deforming surfaces illustrate the effectiveness of the proposed method.

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