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1 – 10 of over 47000
Article
Publication date: 2 January 2019

Ke Zhang, Hao Gui, Zhifeng Luo and Danyang Li

Laser navigation without a reflector does not require setup of reflector markers at the scene and thus has the advantages of free path setting and flexible change. This…

Abstract

Purpose

Laser navigation without a reflector does not require setup of reflector markers at the scene and thus has the advantages of free path setting and flexible change. This technology has attracted wide attention in recent years and shows great potential in the field of automatic logistics, including map building and locating in real-time according to the environment. This paper aims to focus on the application of feature matching for map building.

Design/methodology/approach

First, an improved linear binary relation algorithm was proposed to calculate the local similarity of the feature line segments, and the matching degree matrix of feature line segments between two adjacent maps was established. Further, rough matching for the two maps was performed, and both the initial rotation matrix and the translation vector for the adjacent map matching were obtained. Then, to improve the rotation matrix, a region search optimization algorithm was proposed, which took the initial rotation matrix as the starting point and searched gradually along a lower error-of-objective function until the error sequence was nonmonotonic. Finally, the random-walk method was proposed to optimize the translation vector by iterating until the error-objective function reached the minimum.

Findings

The experimental results show that the final matching error was controlled within 10 mm after both rotation and translation optimization. Also, the algorithm of map matching and optimization proposed in this paper can realize accurately the feature matching of a laser navigation map and basically meet the real-time navigation and positioning requirements for an automated-guided robot.

Originality/value

A linear binary relation algorithm was proposed, and the local similarity between line segments is calculated on the basis of the binary relation. The hill-climbing region search algorithm and the random-walk algorithm were proposed to optimize the rotation matrix and the translation vector, respectively. This algorithm has been applied to industrial production.

Details

Industrial Robot: the international journal of robotics research and application, vol. 46 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 19 June 2017

Qian Sun, Ming Diao, Yibing Li and Ya Zhang

The purpose of this paper is to propose a binocular visual odometry algorithm based on the Random Sample Consensus (RANSAC) in visual navigation systems.

Abstract

Purpose

The purpose of this paper is to propose a binocular visual odometry algorithm based on the Random Sample Consensus (RANSAC) in visual navigation systems.

Design/methodology/approach

The authors propose a novel binocular visual odometry algorithm based on features from accelerated segment test (FAST) extractor and an improved matching method based on the RANSAC. Firstly, features are detected by utilizing the FAST extractor. Secondly, the detected features are roughly matched by utilizing the distance ration of the nearest neighbor and the second nearest neighbor. Finally, wrong matched feature pairs are removed by using the RANSAC method to reduce the interference of error matchings.

Findings

The performance of this new algorithm has been examined by an actual experiment data. The results shown that not only the robustness of feature detection and matching can be enhanced but also the positioning error can be significantly reduced by utilizing this novel binocular visual odometry algorithm. The feasibility and effectiveness of the proposed matching method and the improved binocular visual odometry algorithm were also verified in this paper.

Practical implications

This paper presents an improved binocular visual odometry algorithm which has been tested by real data. This algorithm can be used for outdoor vehicle navigation.

Originality/value

A binocular visual odometer algorithm based on FAST extractor and RANSAC methods is proposed to improve the positioning accuracy and robustness. Experiment results have verified the effectiveness of the present visual odometer algorithm.

Details

Industrial Robot: An International Journal, vol. 44 no. 4
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 17 August 2012

Zhi‐jie Dong, Feng Ye, Di Li and Jie‐xian Huang

The purpose of this paper is to study the application of feature‐based image matching algorithm for PCB matching without using special fiducial marks.

Abstract

Purpose

The purpose of this paper is to study the application of feature‐based image matching algorithm for PCB matching without using special fiducial marks.

Design/methodology/approach

Speed‐up robust feature (SURF) is applied to extract the interest points in PCB images. An advanced threshold is set to reject the interest points with low responses to speed up feature computation. In order to improve the performance for rotation, the descriptors are based on multi‐orientations. The many‐to‐many tentative correspondences are determined with a maximum distance. Hough transform is used to reject the mismatches and the affine parameters are computed with a square‐least solution.

Findings

Results show that the method proposed in this paper can match the PCB images without using special fiducial marks effectively. The image matching algorithm shows a better performance for image rotation than the standard SURF and it succeeds in matching the image including repetitive patterns which will deteriorate the distinctiveness of feature descriptors.

Research limitations/implications

Additional orientations produce more descriptors so that it takes extra time for feature description and matching.

Originality/value

The paper proposes a SURF‐based image matching algorithm to match the PCB images without special fiducial marks. This can reduce the complexity of PCB production. The image matching algorithm is robust to image rotation and repetitive patterns and can be used in other applications of image matching.

Article
Publication date: 22 July 2021

Zirui Guo, Huimin Lu, Qinghua Yu, Ruibin Guo, Junhao Xiao and Hongshan Yu

This paper aims to design a novel feature descriptor to improve the performance of feature matching in challenge scenes, such as low texture and wide-baseline scenes…

Abstract

Purpose

This paper aims to design a novel feature descriptor to improve the performance of feature matching in challenge scenes, such as low texture and wide-baseline scenes. Common descriptors are not suitable for low texture scenes and other challenging scenes mainly owing to encoding only one kind of features. The proposed feature descriptor considers multiple features and their locations, which is more expressive.

Design/methodology/approach

A graph neural network–based descriptors enhancement algorithm for feature matching is proposed. In this paper, point and line features are the primary concerns. In the graph, commonly used descriptors for points and lines constitute the nodes and the edges are determined by the geometric relationship between points and lines. After the graph convolution designed for incomplete join graph, enhanced descriptors are obtained.

Findings

Experiments are carried out in indoor, outdoor and low texture scenes. The experiments investigate the real-time performance, rotation invariance, scale invariance, viewpoint invariance and noise sensitivity of the descriptors in three types of scenes. The results show that the enhanced descriptors are robust to scene changes and can be used in wide-baseline matching.

Originality/value

A graph structure is designed to represent multiple features in an image. In the process of building graph structure, the geometric relation between multiple features is used to establish the edges. Furthermore, a novel hybrid descriptor for points and lines is obtained using graph convolutional neural network. This enhanced descriptor has the advantages of both point features and line features in feature matching.

Details

Industrial Robot: the international journal of robotics research and application, vol. 48 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

Open Access
Article
Publication date: 5 June 2020

Zijun Jiang, Zhigang Xu, Yunchao Li, Haigen Min and Jingmei Zhou

Precise vehicle localization is a basic and critical technique for various intelligent transportation system (ITS) applications. It also needs to adapt to the complex road…

Abstract

Purpose

Precise vehicle localization is a basic and critical technique for various intelligent transportation system (ITS) applications. It also needs to adapt to the complex road environments in real-time. The global positioning system and the strap-down inertial navigation system are two common techniques in the field of vehicle localization. However, the localization accuracy, reliability and real-time performance of these two techniques can not satisfy the requirement of some critical ITS applications such as collision avoiding, vision enhancement and automatic parking. Aiming at the problems above, this paper aims to propose a precise vehicle ego-localization method based on image matching.

Design/methodology/approach

This study included three steps, Step 1, extraction of feature points. After getting the image, the local features in the pavement images were extracted using an improved speeded up robust features algorithm. Step 2, eliminate mismatch points. Using a random sample consensus algorithm to eliminate mismatched points of road image and make match point pairs more robust. Step 3, matching of feature points and trajectory generation.

Findings

Through the matching and validation of the extracted local feature points, the relative translation and rotation offsets between two consecutive pavement images were calculated, eventually, the trajectory of the vehicle was generated.

Originality/value

The experimental results show that the studied algorithm has an accuracy at decimeter-level and it fully meets the demand of the lane-level positioning in some critical ITS applications.

Details

Journal of Intelligent and Connected Vehicles, vol. 3 no. 2
Type: Research Article
ISSN: 2399-9802

Keywords

Article
Publication date: 1 May 2006

Jian Hou, Naiming Qi and Hong Zhang

To present a stereo matching algorithm which satisfies the need of visual navigation on outdoor natural terrain for lunar rover or other mobile robots.

Abstract

Purpose

To present a stereo matching algorithm which satisfies the need of visual navigation on outdoor natural terrain for lunar rover or other mobile robots.

Design/methodology/approach

A feature‐assisted matching algorithm is presented to generate dense and accurate disparity map of natural terrain. Multi‐feature matching strategy produces reliable matching results for edge points. Disparity monotony constraint is derived and other geometrical constraints are introduced. With these constraints the edge‐matching results are used to limit the search region in area‐matching. As a result the algorithm produces dense disparity maps with fairly high accuracy and demonstrates advantages over straightforward area‐matching algorithm in improving matching accuracy.

Findings

With the help of several constraints, the feature‐assisted matching algorithm performs well in the matching of stereo image pairs of natural terrain.

Research limitations/implications

The algorithm focus on improving the accuracy of stereo image pairs matching of natural terrain and computation complexity is not an important designing factor. Only with the assistance of special hardware or other technique can the algorithm be used for real‐time navigation.

Practical implications

The algorithm is able to produce dense disparity map of natural terrain with rather high accuracy and can be used for the navigation of lunar rover or other outdoor mobile robots.

Originality/value

The paper provides a new approach to produce accurate and dense disparity map of natural terrain.

Details

Aircraft Engineering and Aerospace Technology, vol. 78 no. 3
Type: Research Article
ISSN: 0002-2667

Keywords

Article
Publication date: 15 May 2020

Farid Esmaeili, Hamid Ebadi, Mohammad Saadatseresht and Farzin Kalantary

Displacement measurement in large-scale structures (such as excavation walls) is one of the most important applications of close-range photogrammetry, in which achieving…

Abstract

Purpose

Displacement measurement in large-scale structures (such as excavation walls) is one of the most important applications of close-range photogrammetry, in which achieving high precision requires extracting and accurately matching local features from convergent images. The purpose of this study is to introduce a new multi-image pointing (MIP) algorithm is introduced based on the characteristics of the geometric model generated from the initial matching. This self-adaptive algorithm is used to correct and improve the accuracy of the extracted positions from local features in the convergent images.

Design/methodology/approach

In this paper, the new MIP algorithm based on the geometric characteristics of the model generated from the initial matching was introduced, which in a self-adaptive way corrected the extracted image coordinates. The unique characteristics of this proposed algorithm were that the position correction was accomplished with the help of continuous interaction between the 3D model coordinates and the image coordinates and that it had the least dependency on the geometric and radiometric nature of the images. After the initial feature extraction and implementation of the MIP algorithm, the image coordinates were ready for use in the displacement measurement process. The combined photogrammetry displacement adjustment (CPDA) algorithm was used for displacement measurement between two epochs. Micro-geodesy, target-based photogrammetry and the proposed MIP methods were used in a displacement measurement project for an excavation wall in the Velenjak area in Tehran, Iran, to evaluate the proposed algorithm performance. According to the results, the measurement accuracy of the point geo-coordinates of 8 mm and the displacement accuracy of 13 mm could be achieved using the MIP algorithm. In addition to the micro-geodesy method, the accuracy of the results was matched by the cracks created behind the project’s wall. Given the maximum allowable displacement limit of 4 cm in this project, the use of the MIP algorithm produced the required accuracy to determine the critical displacement in the project.

Findings

Evaluation of the results demonstrated that the accuracy of 8 mm in determining the position of the points on the feature and the accuracy of 13 mm in the displacement measurement of the excavation walls could be achieved using precise positioning of local features on images using the MIP algorithm.The proposed algorithm can be used in all applications that need to achieve high accuracy in determining the 3D coordinates of local features in close-range photogrammetry.

Originality/value

Some advantages of the proposed MIP photogrammetry algorithm, including the ease of obtaining observations and using local features on the structure in the images rather than installing the artificial targets, make it possible to effectively replace micro-geodesy and instrumentation methods. In addition, the proposed MIP method is superior to the target-based photogrammetric method because it does not need artificial target installation and protection. Moreover, in each photogrammetric application that needs to determine the exact point coordinates on the feature, the proposed algorithm can be very effective in providing the possibility to achieve the required accuracy according to the desired objectives.

Article
Publication date: 16 October 2018

Shaoyan Xu, Tao Wang, Congyan Lang, Songhe Feng and Yi Jin

Typical feature-matching algorithms use only unary constraints on appearances to build correspondences where little structure information is used. Ignoring structure…

Abstract

Purpose

Typical feature-matching algorithms use only unary constraints on appearances to build correspondences where little structure information is used. Ignoring structure information makes them sensitive to various environmental perturbations. The purpose of this paper is to propose a novel graph-based method that aims to improve matching accuracy by fully exploiting the structure information.

Design/methodology/approach

Instead of viewing a frame as a simple collection of keypoints, the proposed approach organizes a frame as a graph by treating each keypoint as a vertex, where structure information is integrated in edges between vertices. Subsequently, the matching process of finding keypoint correspondence is formulated in a graph matching manner.

Findings

The authors compare it with several state-of-the-art visual simultaneous localization and mapping algorithms on three datasets. Experimental results reveal that the ORB-G algorithm provides more accurate and robust trajectories in general.

Originality/value

Instead of viewing a frame as a simple collection of keypoints, the proposed approach organizes a frame as a graph by treating each keypoint as a vertex, where structure information is integrated in edges between vertices. Subsequently, the matching process of finding keypoint correspondence is formulated in a graph matching manner.

Details

Industrial Robot: An International Journal, vol. 45 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 12 January 2018

Yue Wang, Shusheng Zhang, Sen Yang, Weiping He and Xiaoliang Bai

This paper aims to propose a real-time augmented reality (AR)-based assembly assistance system using a coarse-to-fine marker-less tracking strategy. The system…

Abstract

Purpose

This paper aims to propose a real-time augmented reality (AR)-based assembly assistance system using a coarse-to-fine marker-less tracking strategy. The system automatically adapts to tracking requirement when the topological structure of the assembly changes after each assembly step.

Design/methodology/approach

The prototype system’s process can be divided into two stages: the offline preparation stage and online execution stage. In the offline preparation stage, planning results (assembly sequence, parts position, rotation, etc.) and image features [gradient and oriented FAST and rotated BRIEF (ORB)features] are extracted automatically from the assembly planning process. In the online execution stage, too, image features are extracted and matched with those generated offline to compute the camera pose, and planning results stored in XML files are parsed to generate the assembly instructions for manipulators. In the prototype system, the working range of template matching algorithm, LINE-MOD, is first extended by using depth information; then, a fast and robust marker-less tracker that combines the modified LINE-MOD algorithm and ORB tracker is designed to update the camera pose continuously. Furthermore, to track the camera pose stably, a tracking strategy according to the characteristic of assembly is presented herein.

Findings

The tracking accuracy and time of the proposed marker-less tracking approach were evaluated, and the results showed that the tracking method could run at 30 fps and the position and pose tracking accuracy was slightly superior to ARToolKit.

Originality/value

The main contributions of this work are as follows: First, the authors present a coarse-to-fine marker-less tracking method that uses modified state-of-the-art template matching algorithm, LINE-MOD, to find the coarse camera pose. Then, a feature point tracker ORB is activated to calculate the accurate camera pose. The whole tracking pipeline needs, on average, 24.35 ms for each frame, which can satisfy the real-time requirement for AR assembly. On basis of this algorithm, the authors present a generic tracking strategy according to the characteristics of the assembly and develop a generic AR-based assembly assistance platform. Second, the authors present a feature point mismatch-eliminating rule based on the orientation vector. By obtaining stable matching feature points, the proposed system can achieve accurate tracking results. The evaluation of the camera position and pose tracking accuracy result show that the study’s method is slightly superior to ARToolKit markers.

Details

Assembly Automation, vol. 38 no. 1
Type: Research Article
ISSN: 0144-5154

Keywords

Article
Publication date: 19 June 2009

Chao Wang, Jie Lu and Guangquan Zhang

Matching relevant ontology data for integration is vitally important as the amount of ontology data increases along with the evolving Semantic web, in which data are…

Abstract

Purpose

Matching relevant ontology data for integration is vitally important as the amount of ontology data increases along with the evolving Semantic web, in which data are published from different individuals or organizations in a decentralized environment. For any domain that has developed a suitable ontology, its ontology annotated data (or simply ontology data) from different sources often overlaps and needs to be integrated. The purpose of this paper is to develop intelligent web ontology data matching method and framework for data integration.

Design/methodology/approach

This paper develops an intelligent matching method to solve the issue of ontology data matching. Based on the matching method, it also proposes a flexible peer‐to‐peer framework to address the issue of ontology data integration in a distributed Semantic web environment.

Findings

The proposed matching method is different from existing data matching or merging methods applied to data warehouse in that it employs a machine learning approach and more similarity measurements by exploring ontology features.

Research limitations/implications

The proposed method and framework will be further tested for some more complicated real cases in the future.

Originality/value

The experiments show that this proposed intelligent matching method increases ontology data matching accuracy.

Details

International Journal of Web Information Systems, vol. 5 no. 2
Type: Research Article
ISSN: 1744-0084

Keywords

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