Using a novel multiresolution hybrid matching method to improve stereo matching accuracy of satellite images

2000 ◽  
Author(s):  
Yanwen Ji ◽  
Anthony T. S. Ho ◽  
Tao Yu
Keyword(s):  
Satellite Images ◽  
Stereo Matching ◽  
Matching Method ◽  
Matching Accuracy

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.

Building a Standard 3D Face Database Based on Planar Templates

2011 ◽  
Vol 48-49 ◽  
pp. 280-283
Author(s):  
Xin Xin Li ◽  
Xun Gong
Keyword(s):  
3D Models ◽  
Face Database ◽  
Matching Method ◽  
Matching Accuracy ◽  
Point Matching ◽  
Dense Point ◽  
The Mean ◽  
Point To Point ◽  
3D Face Database ◽  
2D Space

This paper presents a new point matching method to solve the dense point-to-point alignment of scanned 3D faces. Texture maps of 3D models are generated at first by unwrapping 3D faces to 2D space. Then, we build planar templates based on the mean shape computed by a group of annotated texture map. 34 landmarks on the unwrapped texture images are located by AAM and the final correspondence is built according to the templates. Comparing to the traditional algorithms, the presented point matching method can achieve good matching accuracy and stability.

scholarly journals An Efficient Dense Stereo Matching Method for Planetary Rover

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 48551-48564 ◽  
Author(s):  
Haichao Li ◽  
Liang Chen ◽  
Feng Li
Keyword(s):  
Stereo Matching ◽  
Matching Method ◽  
Planetary Rover ◽  
Dense Stereo Matching

scholarly journals Stereo Matching Algorithm Based on 2D Delaunay Triangulation

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Xue-he Zhang ◽  
Ge Li ◽  
Chang-le Li ◽  
He Zhang ◽  
Jie Zhao ◽  
...  
Keyword(s):  
Delaunay Triangulation ◽  
Stereo Matching ◽  
Robot Vision ◽  
Depth Estimation ◽  
Planning System ◽  
Disparity Map ◽  
Matching Method ◽  
Running Speed ◽  
Edge Operator ◽  
Edge Points

To fulfill the applications on robot vision, the commonly used stereo matching method for depth estimation is supposed to be efficient in terms of running speed and disparity accuracy. Based on this requirement, Delaunay-based stereo matching method is proposed to achieve the aforementioned standards in this paper. First, a Canny edge operator is used to detect the edge points of an image as supporting points. Those points are then processed using a Delaunay triangulation algorithm to divide the whole image into a series of linked triangular facets. A proposed module composed of these facets performs a rude estimation of image disparity. According to the triangular property of shared vertices, the estimated disparity is then refined to generate the disparity map. The method is tested on Middlebury stereo pairs. The running time of the proposed method is about 1 s and the matching accuracy is 93%. Experimental results show that the proposed method improves both running speed and disparity accuracy, which forms a steady foundation and good application prospect for a robot’s path planning system with stereo camera devices.

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