Binocular Stereo Matching Algorithm for Wide Baseline Based on Stable Extremal Regions

2007 ◽  
Author(s):  
Zhu-Lin Li ◽  
Zong-Tao Zhao ◽  
Hong-Lei Zhang ◽  
Yan Ma
Keyword(s):  
Stereo Matching ◽  
Matching Algorithm ◽  
Binocular Stereo

Research and Realization of a New Algorithm for Stereo Matching Based on Binocular Vision

2013 ◽  
Vol 670 ◽  
pp. 202-207 ◽  
Author(s):  
Jun Ting Cheng ◽  
C. Zhao ◽  
W.L. Zhao ◽  
W.H. Wu
Keyword(s):  
Binocular Vision ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Cnc Machining ◽  
Matching Algorithm ◽  
Evaluation Test ◽  
Three Dimensional Measurement ◽  
Binocular Stereo ◽  
Measuring Machine ◽  
3D Solid

In the development of a three-dimensional measurement system, binocular stereo matching is the most important and difficult. In the basis of introducing selective principles of matching algorithm, a new stereo matching algorithm for binocular vision is put forward that is named noncoded difference measuring distance. The algorithm effectively grapples with the problem of searching for the coincidence relation of raster and can efficiently and accurately obtain three-dimensional world coordinates of the entities. Experiment results show that this 3D measuring machine can effectively measure the 3D solid profile of free surface. During the evaluation test for accuracy, scan a standard plane. Fit all 3D points in one plane, and then the flatness value of this plane is obtained. The flatness value of the standard plane has been ultimately measured as: ± 0.0462mm, this measuring accuracy can completely satisfy the requirements of rapid prototyping or CNC machining, it as well as achieves the stated accuracy (± 0.05mm).

scholarly journals A Real-Time Range Finding System with Binocular Stereo Vision

10.5772/50921 ◽  
2012 ◽  
Vol 9 (1) ◽  
pp. 26 ◽  
Author(s):  
Xiao-Bo Lai ◽  
Hai-Shun Wang ◽  
Yue-Hong Xu
Keyword(s):  
Real Time ◽  
Stereo Vision ◽  
Stereo Matching ◽  
Single Point ◽  
Time Range ◽  
Real Time Control ◽  
Matching Algorithm ◽  
Range Finding ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

To acquire range information for mobile robots, a TMS320DM642 DSP-based range finding system with binocular stereo vision is proposed. Firstly, paired images of the target are captured and a Gaussian filter, as well as improved Sobel kernels, are achieved. Secondly, a feature-based local stereo matching algorithm is performed so that the space location of the target can be determined. Finally, in order to improve the reliability and robustness of the stereo matching algorithm under complex conditions, the confidence filter and the left-right consistency filter are investigated to eliminate the mismatching points. In addition, the range finding algorithm is implemented in the DSP/BIOS operating system to gain real-time control. Experimental results show that the average accuracy of range finding is more than 99% for measuring single-point distances equal to 120cm in the simple scenario and the algorithm takes about 39ms for ranging a time in a complex scenario. The effectivity, as well as the feasibility, of the proposed range finding system are verified.

Research of Stereo Matching Based on HALCON

2013 ◽  
Vol 415 ◽  
pp. 361-364
Author(s):  
Hui Yu Xiang ◽  
Zhe Li ◽  
Jia Jun Huang ◽  
Baoan Han
Keyword(s):  
Image Matching ◽  
Stereo Matching ◽  
Vision System ◽  
Difficult Problem ◽  
Matching Method ◽  
Matching Accuracy ◽  
Matching Algorithm ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Matching Window

Binocular stereo matching is a hot and difficult problem in machine vision. In this paper, based on the matching method of Halcon which is visual software perform image matching. First, performing binocular stereo vision system calibration, based on the calibration results acquired the epipolar standard geometric structure. Then, image matching researched under this structure. At last, using ncc matching algorithm, through comparing the different parameters matching window obtain ideal match results. Experiments prove that this method not only can effectively shorten matching time, but also can achieve higher matching accuracy.

Regional fuzzy binocular stereo matching algorithm based on global correlation coding for 3D measurement of rail surface

Optik ◽  
2020 ◽  
Vol 207 ◽  
pp. 164488 ◽  
Author(s):  
Zhaoxin Wang ◽  
Jiang Yue ◽  
Jing Han ◽  
Yong Jin ◽  
Baoming Li
Keyword(s):  
Stereo Matching ◽  
3D Measurement ◽  
Matching Algorithm ◽  
Global Correlation ◽  
Binocular Stereo

Analysis and Research of Stereo Correspondence Algorithms

2014 ◽  
Vol 568-570 ◽  
pp. 768-772
Author(s):  
Yan Yun Li ◽  
Zhao Hui Liu ◽  
Liang Zhou
Keyword(s):  
Computer Vision ◽  
Vision Research ◽  
Stereo Matching ◽  
Technology Development ◽  
Stereo Correspondence ◽  
Matching Algorithm ◽  
Binocular Stereo ◽  
Key Techniques

Stereo matching has been the focus of computer vision research. Some current researches on stereo matching algorithms were summarized, the stereo matching key techniques were analyzed; View of the current major challenges on binocular stereo matching, elaborated matching algorithm possible solutions and modification approaches; Finally, the field of technology development are prospected.

scholarly journals An Improved Stereo Matching Algorithm for Vehicle Speed Measurement System Based on Spatial and Temporal Image Fusion

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 866
Author(s):  
Lei Yang ◽  
Qingyuan Li ◽  
Xiaowei Song ◽  
Wenjing Cai ◽  
Chunping Hou ◽  
...  
Keyword(s):  
Image Fusion ◽  
Measurement System ◽  
Stereo Matching ◽  
License Plate ◽  
Vehicle Speed ◽  
Matching Algorithm ◽  
Speed Measurement ◽  
Optimum Speed ◽  
Binocular Stereo ◽  
Plate Area

This paper proposes an improved stereo matching algorithm for vehicle speed measurement system based on spatial and temporal image fusion (STIF). Firstly, the matching point pairs in the license plate area with obviously abnormal distance to the camera are roughly removed according to the characteristic of license plate specification. Secondly, more mismatching point pairs are finely removed according to local neighborhood consistency constraint (LNCC). Thirdly, the optimum speed measurement point pairs are selected for successive stereo frame pairs by STIF of binocular stereo video, so that the 3D points corresponding to the matching point pairs for speed measurement in the successive stereo frame pairs are in the same position on the real vehicle, which can significantly improve the vehicle speed measurement accuracy. LNCC and STIF can be used not only for license plate, but also for vehicle logo, light, mirror etc. Experimental results demonstrate that the vehicle speed measurement system with the proposed LNCC+STIF stereo matching algorithm can significantly outperform the state-of-the-art system in accuracy.

scholarly journals Binocular stereo matching algorithm based on MST cost aggregation

2021 ◽  
Vol 18 (4) ◽  
pp. 3215-3226
Author(s):  
Jian Zhang ◽  
◽  
Yan Zhang ◽  
Cong Wang ◽  
Huilong Yu ◽  
...  
Keyword(s):  
Stereo Matching ◽  
Matching Algorithm ◽  
Cost Aggregation ◽  
Binocular Stereo

Binocular Stereo Matching Algorithm Based on Multidimensional Feature Fusion

2020 ◽  
Vol 57 (16) ◽  
pp. 161501
Author(s):  
龚伟 Gong Wei ◽  
秦岭 Qin Ling ◽  
任高峰 Ren Gaofeng ◽  
周博 Zhou Bo
Keyword(s):  
Stereo Matching ◽  
Feature Fusion ◽  
Matching Algorithm ◽  
Binocular Stereo
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