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.

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.

3D Laser Remanufacturing of Damaged Parts

2013 ◽  
Vol 690-693 ◽  
pp. 3350-3353
Author(s):  
Yan Fang ◽  
Xi Chen Yang ◽  
Jian Bo Lei
Keyword(s):  
Path Planning ◽  
Image Matching ◽  
Point Cloud ◽  
Vision System ◽  
Processing Parameters ◽  
Point Cloud Data ◽  
Robot System ◽  
Cloud Data ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

A repair method for damaged parts based on laser robot system is proposed. First, to obtain 3D point cloud in the robot coordinate system, damaged part surfaces are scanned with binocular stereo vision system, including camera calibration and image matching. Secondly, with the point cloud data and laser processing parameters, system accomplishes path planning, generates robot programs. Experimental results show that system can effectively achieves 3D reconstruction and path planning, which further enable high precision remanufacturing.

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.

Vision-Based Aerial Refueling Docking Based on SURF Algorithm

2011 ◽  
Vol 130-134 ◽  
pp. 3102-3106
Author(s):  
Si Yuan Qin ◽  
Jian Guo Yan
Keyword(s):  
Vision System ◽  
Three Dimensional ◽  
Spatial Position ◽  
Target Point ◽  
Feature Points ◽  
Aerial Refueling ◽  
Matching Algorithm ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Left And Right

For the Boom and Receptacle Air Refueling, in order to locate the spatial position of the refueling receptacle, an object locating method is developed based on Speeded-up Robust Feature (SURF) algorithm. Firstly, SURF feature vector matching algorithm is used to detect and collect suitable SURF feature points in left and right images produced by binocular stereo vision system separately. Then the point that shows the same spatial position in both left and right images can be located through process such as deleting wrong matching points and calculating the image coordinate of the target point. Finally, the three-dimensional coordinates of the target points could be rebuilt in the camera’s coordinate system. According to the results of experiments, this method has good robustness and practicability.

Study on a New Sine Raster Generating Algorithm for Phase-Based Matching

2010 ◽  
Vol 29-32 ◽  
pp. 2633-2638
Author(s):  
Xiao Hui Liu ◽  
Kai Yong Jiang ◽  
Jun Yi Lin
Keyword(s):  
Stereo Matching ◽  
Phase Distribution ◽  
Gamma Correction ◽  
Matching Method ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Pair Matching ◽  
Efficient Matching ◽  
Influence Of Noise ◽  
Experiment Analysis

Phase-based Stereo Matching (PSM) is an efficient matching method in binocular stereo vision. It bases on correspondence points which have the same phase-distribution. Sine raster generating algorithm is a basic and important step in PSM study. This paper advances that using defocusing rectify-binary patterns (DRBP) method substituted the focusing-sinusoidal-patterns (FSP) method. It has following advantages: (1) No gamma correction is required; (2) The object illuminance measurement is not desired; (3) The influence of noise is minified. There are same phases distribution in correspond points of the pair matching lines by experiment analysis. The feasibility of using DRBP to generate sine raster in PSM is demonstrated.

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.

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).

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