Stereo Matching Algorithm Based on Edge Feature of Segmented Image

2013 ◽  
Vol 333-335 ◽  
pp. 948-953
Author(s):  
Yi Zhang ◽  
Cheng Liang Huang ◽  
Lian Fa Bai
Keyword(s):  
Stereo Matching ◽  
Mean Shift ◽  
Weighting Factor ◽  
Reference Image ◽  
Matching Accuracy ◽  
Matching Algorithm ◽  
Mean Shift Algorithm ◽  
Fast Speed ◽  
Segmented Image ◽  
Edge Feature

Stereo matching of the disparity discontinuous boundaries and weak texture regions is still a problem of computer vision. Local-based stereo matching algorithm with the advantages of fast speed and high accuracy is the most common method. In order to improve the matching accuracy of the mentioned regions,a stereo matching algorithm based on edge feature of segmented image is proposed. Firstly, the reference image was segmented by Mean-Shift algorithm. Then, support window was dynamically allocated based on edge feature of segmented image. Finally, the disparity distribution of support window was adjusted by introducing weighting factor. The experimental results show that this algorithm can reduce noise and effectively improve the matching accuracy.

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.

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.

Multi-Scale Edge Extraction Based Stereo Matching Algorithm

2010 ◽  
Vol 44-47 ◽  
pp. 4162-4166
Author(s):  
Jing Lian ◽  
Lin Hui Li ◽  
Xiao Yong Shen ◽  
Xian Peng Hao
Keyword(s):  
Stereo Matching ◽  
Robot Vision ◽  
Outdoor Environment ◽  
Linear Filter ◽  
Edge Extraction ◽  
Matching Algorithm ◽  
Multi Scale ◽  
Feature Based ◽  
3D Information ◽  
Edge Feature

In the field of robot vision, edge feature based stereo matching algorithm can reconstruct the targets with clear contours, which needs accurate and continuous target edges been extracted. In the paper, the smoothing filter operator was designed based on the discrete criteria of edge extraction and its correspondence optimal linear filter. Edge extraction was carried out incorporated the nonmaximum suppression and two thresholds techniques. The discrete criteria based multi-scale edge extraction method was studied with full use of the multi-scale character of the edge information. The detected multi-scale edges were synthesized to obtain the accurate and continuous single pixel wide edge. Then an edge feature based stereo matching algorithm was proposed to obtain 3D information of target. The experimental results demonstrate that the method can effectively suppress disturbance in outdoor environment and reconstruct target contour clearly.

scholarly journals A Line-Based Adaptive-Weight Matching Algorithm Using Loopy Belief Propagation

2015 ◽  
Vol 2015 ◽  
pp. 1-13
Author(s):  
Hui Li ◽  
Xiao-Guang Zhang ◽  
Zheng Sun
Keyword(s):  
Stereo Matching ◽  
Belief Propagation ◽  
Mean Shift ◽  
Spatial Proximity ◽  
Consistency Checking ◽  
Disparity Map ◽  
Matching Effect ◽  
Matching Algorithm ◽  
Adaptive Weight ◽  
Loopy Belief Propagation

In traditional adaptive-weight stereo matching, the rectangular shaped support region requires excess memory consumption and time. We propose a novel line-based stereo matching algorithm for obtaining a more accurate disparity map with low computation complexity. This algorithm can be divided into two steps: disparity map initialization and disparity map refinement. In the initialization step, a new adaptive-weight model based on the linear support region is put forward for cost aggregation. In this model, the neural network is used to evaluate the spatial proximity, and the mean-shift segmentation method is used to improve the accuracy of color similarity; the Birchfield pixel dissimilarity function and the census transform are adopted to establish the dissimilarity measurement function. Then the initial disparity map is obtained by loopy belief propagation. In the refinement step, the disparity map is optimized by iterative left-right consistency checking method and segmentation voting method. The parameter values involved in this algorithm are determined with many simulation experiments to further improve the matching effect. Simulation results indicate that this new matching method performs well on standard stereo benchmarks and running time of our algorithm is remarkably lower than that of algorithm with rectangle-shaped support region.

Stereo Matching Algorithm Based on Belief Propagation System

2015 ◽  
Vol 713-715 ◽  
pp. 1931-1934
Author(s):  
Si Chen Pan
Keyword(s):  
Computer Vision ◽  
Global Optimization ◽  
Information Transmission ◽  
Optimization Algorithm ◽  
Stereo Matching ◽  
Belief Propagation ◽  
Global Optimization Algorithm ◽  
Matching Accuracy ◽  
Matching Algorithm ◽  
Stereo Reconstruction

Stereo matching methods are widely used in computer vision and stereo reconstruction, from the perspective of improving the matching accuracy, this paper focuses on the global optimization algorithm. An improved Belief Propagation method is proposed in this paper, by involving more pixels into information transmission, our method improves the accuracy ofstereo matching. The experimental results verify the efficiencyand reliability of our method.

Aligning Genomic Sequence Applied in Stereo Matching

2011 ◽  
Vol 121-126 ◽  
pp. 4357-4361
Author(s):  
Shu Chun Yu ◽  
Xiao Yang Yu ◽  
Jian Ying Fan ◽  
Hai Bin Wu
Keyword(s):  
Stereo Matching ◽  
Genomic Sequence ◽  
Experimental Results ◽  
Genomic Sequences ◽  
Control Points ◽  
Matching Method ◽  
Matching Algorithm ◽  
Fast Speed

The stereo matching algorithm based on aligning genomic sequence is proposed in the paper. This method is divided in three steps: do genomic sequence on the same name epipolar of stereo matching, get branch matrix by establishing genomic sequences using the same name epipolar after being genomic sequences, control points technology and dynamic backdate method to get disparity. The experimental results show that stereo matching method based on genomic sequences has fast speed and good matching quality.

scholarly journals Stereo Matching Algorithm Based on HSV Color Space and Improved Census Transform

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Chen Lv ◽  
Jiahan Li ◽  
Qiqi Kou ◽  
Huandong Zhuang ◽  
Shoufeng Tang
Keyword(s):  
Confidence Interval ◽  
Stereo Matching ◽  
Color Space ◽  
Absolute Difference ◽  
Cost Calculation ◽  
Matching Accuracy ◽  
Matching Algorithm ◽  
Hsv Color Space ◽  
Census Transform ◽  
The Cost

Aiming at the problem that stereo matching accuracy is easily affected by noise and amplitude distortion, a stereo matching algorithm based on HSV color space and improved census transform is proposed. In the cost calculation stage, the color image is first converted from RGB space to HSV space; moreover, the hue channel is used as the matching primitive to establish the hue absolute difference (HAD) cost calculation function, which reduces the amount of calculation and enhances the robustness of matching. Then, to solve the problem of the traditional census transform overrelying on the central pixel and to improve the noise resistance of the algorithm, an improved census method based on neighborhood weighting is also proposed. Finally, the HAD cost and the improved census cost are nonlinearly fused as the initial cost. In the aggregation stage, an outlier elimination method based on confidence interval is proposed. By calculating the confidence interval of the aggregation window, this paper eliminates the cost value that is not in the confidence interval and subsequently filters as well as aggregates the remaining costs to further reduce the noise interference and improve the matching accuracy. Experiments show that the proposed method can not only effectively suppress the influence of noise, but also achieve a more robust matching effect in scenes with changing exposure and lighting conditions.

Automatic vertebra segmentation based on graph cut and mean shift algorithm

2011 ◽  
Vol 31 (3) ◽  
pp. 760-762
Author(s):  
Ji LIU ◽  
Xiao-dong KANG ◽  
Fu-cang JIA
Keyword(s):  
Mean Shift ◽  
Graph Cut ◽  
Mean Shift Algorithm
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