Binocular Stereo Matching Method Based on Parallax Waveform Analysis and Conjoint Measurement of Saliency Map

2014 ◽  
Vol 519-520 ◽  
pp. 655-660
Author(s):  
Jing Han ◽  
Zhuang Zhao ◽  
Jiang Yue ◽  
Yi Zhang ◽  
Lian Fa Bai
Keyword(s):  
Stereo Matching ◽  
Saliency Map ◽  
Waveform Analysis ◽  
Conjoint Measurement ◽  
Natural Scene ◽  
Matching Method ◽  
Computation Cost ◽  
Matching Algorithm ◽  
Binocular Stereo ◽  
Global Algorithm

In this paper, we propose a coarse-fine matching algorithm based on parallax waveform analysis and conjoint measurement, which aims at performing the binocular stereo matching in natural scene. For the reason that human only notices the most saliency parts in image, we first extract the saliency areas of the two images, which suppresses the interference of background and reduces the computation cost. According to the saliency map, a global algorithm based on parallax waveform analysis is proposed to achieve the best coarse matching. On this basis, the fine matching is completed by analyzing the local features with the conjoint measurement of SAD and SSIM, which further improves the accuracy in binocular stereo matching. The performance of our algorithm is well demonstrated by experiments.

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.

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.

Binocular stereo matching method based on structure tensor

2016 ◽  
Author(s):  
Xiaowei Song ◽  
Manyi Yang ◽  
Yubo Fan ◽  
Lei Yang
Keyword(s):  
Stereo Matching ◽  
Structure Tensor ◽  
Matching Method ◽  
Binocular Stereo

A Multi-Gradation Stereo Matching Method Based on Edge Feature Points

2013 ◽  
Vol 748 ◽  
pp. 624-628
Author(s):  
Zhu Lin Li
Keyword(s):  
Object Recognition ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Feature Points ◽  
Image Pair ◽  
Three Dimensional Reconstruction ◽  
Matching Method ◽  
Matching Algorithm ◽  
Dimensional Reconstruction ◽  
Edge Feature

A gradation stereo matching algorithm based on edge feature points was proposed. Its basic idea is: firstly edge feature points of image pair were extracted; then, gradient invariability and singular eigenvalue invariability were analyzed, two-grade stereo matching method was build, foundation matrix was solved further, and three-grade stereo matching algorithm was finished by foundation matrix guidance. The result indicates that the algorithm can improve matching precision, from 58.3% to 73.2%, it is simple and utility, and it is important for object recognition, tracking, and three-dimensional reconstruction.

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.

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