Stereo Image Matching Based on SURF Descriptor

2015 ◽  
Vol 1083 ◽  
pp. 142-147
Author(s):  
Luan Zeng ◽  
You Zhai
Keyword(s):  
Image Matching ◽  
Euclidean Distance ◽  
Small Neighborhood ◽  
Stereo Image ◽  
Epipolar Line ◽  
Matching Method ◽  
Matching Efficiency ◽  
Stereo Image Matching ◽  
Calibration Parameters ◽  
Better Than

In order to improve the robustness performance of SURF descriptor applied to stereo image matching, a new matching method is proposed. By using the ratio of minimum to second min Euclidean distance of corresponding features, we can get the coarse matching points aggregation. Then, the epipolar line is computed from calibration parameters. Correspondences are taken as correct correspondences, only if they fall into a small neighborhood of their epipolar line. Taken errors into account, the neighborhood is set (-3, 3). Using this restriction, we can get the correct matching points aggregation. The experimental results show that the correct matches and matching efficiency are better than RANSAC.

A stereo image matching method to improve the DSM accuracy inside building boundaries

2013 ◽  
Vol 39 (4) ◽  
pp. 308-317 ◽  
Author(s):  
Chuiqing Zeng ◽  
Jinfei Wang ◽  
Peijun Shi
Keyword(s):  
Image Matching ◽  
Stereo Image ◽  
Matching Method ◽  
Stereo Image Matching

scholarly journals Stereo Image Matching for Vehicle-Borne Mobile Mapping System Based on Digital Parallax Model

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Ka Zhang ◽  
Yehua Sheng ◽  
Chun Ye
Keyword(s):  
Image Matching ◽  
Stereo Image ◽  
Epipolar Line ◽  
Mobile Mapping ◽  
Dense Matching ◽  
Mapping System ◽  
Mobile Mapping System ◽  
Image Pairs ◽  
Stereo Image Matching ◽  
Speed And Accuracy

Considering automatic and effective stereo image matching for vehicle-borne mobile mapping system (VMMS), a new stereo image matching algorithm based on digital parallax model (DPM) is proposed in this paper. The new matching propagation strategy is designed in this algorithm, which includes two processes as DPM construction and parallax prediction. With some known matched points, the DPM of stereo image pairs is firstly constructed, and parameters for confirming conjugate epipolar line is also worked out. Then searching range during dense matching can be confirmed under constraints of DPM and epipolar line, which can improve matching speed and accuracy. Furthermore, to improve matching robustness, the computation model of similarity measurement combined with local structure feature and global color feature is designed. The new algorithm is applied to actual stereo images taken by VMMS to verify its validity. Experimental results show that the proposed approach has higher reliability and accuracy.

Reconstruction and quantitative analysis of metallic surfaces with pits based on improved stereo image matching method

2011 ◽  
Vol 47 (2) ◽  
pp. 255-263 ◽  
Author(s):  
B. P. Rusyn ◽  
Ya. Yu. Varets’kyi ◽  
Yu. V. Lysak ◽  
A. Yu. Pokhmurs’kyi
Keyword(s):  
Quantitative Analysis ◽  
Image Matching ◽  
Stereo Image ◽  
Metallic Surfaces ◽  
Matching Method ◽  
Stereo Image Matching

Research on the Algorithm of Image Matching Based on Improved SIFT

2014 ◽  
Vol 686 ◽  
pp. 348-353
Author(s):  
Xiang Chen Qiao
Keyword(s):  
Image Matching ◽  
Euclidean Distance ◽  
Layout Optimization ◽  
Image Stitching ◽  
Matching Method ◽  
Matching Accuracy ◽  
Sift Algorithm ◽  
Matching Efficiency ◽  
Basic Characteristics

The paper analyze and improve the SIFT optimized algorithm, and proposes an image matching method for SIFT algorithm based on quasi Euclidean distance and KD-tree. Experiments show that this algorithm has matching more points, high matching accuracy, no repeated points and higher advantage of matching efficiency based on keeping the basic characteristics of SIFT algorithm unchanged, and provides precise matching point to generate precise image stitching and other related fields of the follow-up product. At the same time, this method was applied to the layout optimization and achieved good results.

scholarly journals Digital Surface Model Interpolation Based on 3D Mesh Models

2018 ◽  
Vol 11 (1) ◽  
pp. 24 ◽  
Author(s):  
Soohyeon Kim ◽  
Sooahm Rhee ◽  
Taejung Kim
Keyword(s):  
Image Matching ◽  
3D Visualization ◽  
Interpolation Method ◽  
Stereo Image ◽  
Distribution Model ◽  
Surface Model ◽  
Digital Surface Model ◽  
3D Mesh ◽  
Stereo Image Matching ◽  
Mesh Models

A digital surface model (DSM) is an important geospatial infrastructure used in various fields. In this paper, we deal with how to improve the quality of DSMs generated from stereo image matching. During stereo image matching, there are outliers due to mismatches, and non-matching regions due to match failure. Such outliers and non-matching regions have to be corrected accurately and efficiently for high-quality DSM generation. This process has been performed by applying a local distribution model, such as inverse distance weight (IDW), or by forming a triangulated irregular network (TIN). However, if the area of non-matching regions is large, it is not trivial to interpolate elevation values using neighboring cells. In this study, we proposed a new DSM interpolation method using a 3D mesh model, which is more robust to outliers and large holes. We compared mesh-based DSM with IDW-based DSM and analyzed the characteristics of each. The accuracy of the mesh-based DSM was a 2.80 m root mean square error (RMSE), while that for the IDW-based DSM was 3.22 m. While the mesh-based DSM successfully removed empty grid cells and outliers, the IDW-based DSM had sharper object boundaries. Because of the nature of surface reconstruction, object boundaries appeared smoother on the mesh-based DSM. We further propose a method of integrating the two DSMs. The integrated DSM maintains the sharpness of object boundaries without significant accuracy degradation. The contribution of this paper is the use of 3D mesh models (which have mainly been used for 3D visualization) for efficient removal of outliers and non-matching regions without a priori knowledge of surface types.

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