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An Enhanced DV-Hop Positioning Scheme Based on Spring Model and Reliable Beacon Node Set

COMPUTER NETWORKS 2022年第0期209卷 1页

作者： Chen, Tianfei Hou, Shuaixin Sun, Lijun Henan Univ Technol Key Lab Grain Informat Proc & Control Minist Educ Zhengzhou 450001 Peoples R China Henan Univ Technol Henan Key Lab Grain Photoelect Detect & Control Zhengzhou 450001 Peoples R China Henan Univ Technol Coll Informat Sci & Engn Zhengzhou 450001 Peoples R China Henan Univ Technol Zhengzhou 450001 Henan Peoples R China

How to get the node position, as a hotter topic in the field of wireless communication, is the primary problem to be solved in wireless sensor networks (WSNs). The DV-Hop positioning scheme is a kind of range-free positioning scheme, which has been favored by researchers in recent years. However, the original DV-Hop scheme faces the shortcoming of low positioning precision and stability. To ameliorate the positioning capability of the DV-Hop, an enhanced DV-Hop scheme based on the spring model and reliable beacon node set has been presented in this paper. Firstly, the relationship between nodes in the network is abstracted as a spring model, and the distance between unknown nodes and beacon nodes is corrected by comprehensively considering the influence of each beacon node from the physical phenomenon of force vector decomposition. After that, based on the random sample consensus (ransac) algorithm, the reliable beacon nodes with smaller distance deviation to the unknown node are picked out to compute the unknown node coordinates, rather than all beacon nodes participating in the calculation. Finally, extensive experiments have been conducted on distance accuracy and positioning performance. Simulation results demonstrate that our proposed positioning scheme outperforms better than original DV-Hop and other existing improved schemes under different scenarios.

关键词： DV-Hop scheme WSN Distance precision Positioning accuracy ransac algorithm

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Depth segmentation in real-world scenes based on U-V disparity analysis

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2020年 73卷 102920-102920页

作者： Li, Xiaohan Chen, Lu Li, Shuang Zhou, Xiang Xi An Jiao Tong Univ Sch Mech Engn 28 Xianning West Rd Xian 710049 Peoples R China Xi An Jiao Tong Univ Sch Food Equipment Engn & Sci 28 Xianning West Rd Xian 710049 Peoples R China

Depth segmentation has the challenge of separating the objects from their supporting surfaces in a noisy environment. To address the issue, a novel segmentation scheme based on disparity analysis is proposed. First, we transform a depth scene into the corresponding U-V disparity map. Then, we conduct a region-based detection method to divide the object region into several targets in the processed U-disparity map. Thirdly, the horizontal plane regions may be mapped as slant lines in the V-disparity map, the Random Sample Consensus (ransac) algorithm is improved to fit such multiple lines. Moreover, noise regions are reduced by image processing strategies during the above processes. We respectively evaluate our approach on both real-world scenes and public data sets to verify the flexibility and generalization. Sufficient experimental results indicate that the algorithm can efficiently segment and label a full-view scene into a group of valid regions as well as removing surrounding noise regions.

关键词： Depth scene segmentation U-V disparity map Projection characteristics analysis Object detection ransac algorithm

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Harmonic Contribution Assessment Based on the Random Sample Consensus and Recursive Least Square Methods

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ENERGIES 2022年第17期15卷 6448-6448页

作者： Park, Jong-Il Park, Chang-Hyun Pukyong Natl Univ Coll Engn Sch Elect Engn 45 Yongso Ro Busan 48513 South Korea

This paper deals with a method of quantifying the harmonic contribution of each harmonic source to system voltage distortion. Assessing the harmonic contribution of individual harmonic sources is essential for mitigating and managing system harmonic levels. Harmonic contributions can be evaluated using the principle of voltage superposition with equivalent voltage models for harmonic sources. In general, the parameters of equivalent voltage models are estimated numerically because it is difficult to measure them directly. In this paper, we present an effective method for estimating equivalent model parameters based on the random sample consensus (ransac) and recursive least square (RLS) with a variable forgetting factor. The procedure for quantifying harmonic contributions using equivalent models is also introduced. Additionally, we propose a network diagram of harmonic contributions that makes it easy to understand the harmonic distortion contributions of all harmonic sources.

关键词： harmonic contribution diagram harmonic distortion outlier ransac algorithm recursive least square method

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Ice Velocity in Upstream of Heilongjiang Based on UAV Low-Altitude Remote Sensing and the SIFT algorithm

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WATER 2022年第12期14卷 1957-1957页

作者： Wang, Enliang Hu, Shengbo Han, Hongwei Li, Yuang Ren, Zhifeng Du, Shilin Northeast Agr Univ Sch Water Conservancy & Civil Engn Harbin 150030 Peoples R China Heilongjiang Prov Key Lab Water Resources & Water Harbin 150030 Peoples R China

In river management, it is important to obtain ice velocity quickly and accurately during ice flood periods. However, traditional ice velocity monitoring methods require buoys, which are costly and inefficient to distribute. It was found that UAV remote sensing images combined with machine vision technology yielded obvious practical advantages in ice velocity monitoring. Current research has mainly monitored sea ice velocity through GPS or satellite remote sensing technology, with few reports available on river ice velocity monitoring. Moreover, traditional river ice velocity monitoring methods are subjective. To solve the problems of existing time-consuming and inaccurate ice velocity monitoring methods, a new ice velocity extraction method based on UAV remote sensing technology is proposed in this article. In this study, the Mohe River section in Heilongjiang Province was chosen as the research area. High-resolution orthoimages were obtained with a UAV during the ice flood period, and feature points in drift ice images were then extracted with the scale-invariant feature transform (SIFT) algorithm. Moreover, the extracted feature points were matched with the brute force (BF) algorithm. According to optimization results obtained with the random sample consensus (ransac) algorithm, the motion trajectories of these feature points were tracked, and an ice displacement rate field was finally established. The results indicated that the average ice velocities in the research area reached 2.00 and 0.74 m/s, and the maximum ice velocities on the right side of the river center were 2.65 and 1.04 m/s at 16:00 on 25 April 2021 and 8:00 on 26 April 2021, respectively. The ice velocity decreased from the river center toward the river banks. The proposed ice velocity monitoring technique and reported data in this study could provide an effective reference for the prediction of ice flood disasters.

关键词： unmanned aerial vehicles SIFT algorithm brutal force matching ransac algorithm ice velocity

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Intelligent Interpretation of the Geometric Properties of Rock Mass Discontinuities Based on an Unmanned Aerial Vehicle

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FRONTIERS IN EARTH SCIENCE 2021年 9卷

作者： Chen, Na Du, Chang-jie Ding, Xiang Hubei Univ Technol Sch Civil Engn Architecture & Environm Wuhan Peoples R China Hubei Univ Technol Sino French Joint Res Collaborat Geomech & Concre Wuhan Peoples R China

The geometric properties of rock mass discontinuities are essential for the evaluation of the safety of rock masses. Numerous studies have recently been performed on the extraction of discontinuity information. However, most methods are characterized by poor data collection and processing efficiency. This paper presents a UAV-based methodology for the accurate and complete acquisition of rock surface data, as well as the automatic extraction of discontinuity information. Moreover, a program called Random Sample Consensus (ransac) Discontinuity Detection (RDD) is developed to extract discontinuity information based on the proposed method. The conclusions of this research are as follows. 1) ransac Discontinuity Detection (RDD) can identify the feature point set of discontinuities from a raw point cloud, and can calculate the discontinuity orientation. 2) The boundary of a discontinuity can be precisely depicted using the improved Graham scan algorithm. 3) The orientations of marked discontinuities extracted by RDD are compared with those extracted by the three-point method in CloudCompare. The differences in the orientations extracted by the two methods are found to be less than 3 degrees for flat discontinuities and only about 4.87 degrees for rough discontinuities, which are within a reasonable error range in practical engineering applications. Therefore, the feasibility of the proposed method is verified.

关键词： UAV technique point cloud automatic extraction discontinuity ransac algorithm

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An Improved ASIFT Image Feature Matching algorithm Based on POS Information

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SENSORS 2022年第20期22卷 7749-7749页

作者： Gao, Junchai Sun, Zhen Xian Technol Univ Sch Elect Informat Engn Xian 710021 Peoples R China

The affine scale-invariant feature transform (ASIFT) algorithm is a feature extraction algorithm with affinity and scale invariance, which is suitable for image feature matching using unmanned aerial vehicles (UAVs). However, there are many problems in the matching process, such as the low efficiency and mismatching. In order to improve the matching efficiency, this algorithm firstly simulates image distortion based on the position and orientation system (POS) information from real-time UAV measurements to reduce the number of simulated images. Then, the scale-invariant feature transform (SIFT) algorithm is used for feature point detection, and the extracted feature points are combined with the binary robust invariant scalable keypoints (BRISK) descriptor to generate the binary feature descriptor, which is matched using the Hamming distance. Finally, in order to improve the matching accuracy of the UAV images, based on the random sample consensus (ransac) a false matching eliminated algorithm is proposed. Through four groups of experiments, the proposed algorithm is compared with the SIFT and ASIFT. The results show that the algorithm can optimize the matching effect and improve the matching speed.

关键词： UAV image feature matching ASIFT algorithm BRISK descriptor ransac algorithm

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MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data

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BMC BIOINFORMATICS 2010年第1期11卷 1-11页

作者： Pluskal, Tomas Castillo, Sandra Villar-Briones, Alejandro Oresic, Matej OIST Cell Unit G0 Okinawa Japan VTT Tech Res Ctr Finland Espoo Finland

Background: Mass spectrometry (MS) coupled with online separation methods is commonly applied for differential and quantitative profiling of biological samples in metabolomic as well as proteomic research. Such approaches are used for systems biology, functional genomics, and biomarker discovery, among others. An ongoing challenge of these molecular profiling approaches, however, is the development of better data processing methods. Here we introduce a new generation of a popular open-source data processing toolbox, MZmine 2. Results: A key concept of the MZmine 2 software design is the strict separation of core functionality and data processing modules, with emphasis on easy usability and support for high-resolution spectra processing. Data processing modules take advantage of embedded visualization tools, allowing for immediate previews of parameter settings. Newly introduced functionality includes the identification of peaks using online databases, MSn data support, improved isotope pattern support, scatter plot visualization, and a new method for peak list alignment based on the random sample consensus (ransac) algorithm. The performance of the ransac alignment was evaluated using synthetic datasets as well as actual experimental data, and the results were compared to those obtained using other alignment algorithms. Conclusions: MZmine 2 is freely available under a GNU GPL license and can be obtained from the project website at: http://***/. The current version of MZmine 2 is suitable for processing large batches of data and has been applied to both targeted and non-targeted metabolomic analyses.

关键词： Mass Spectrometry Data Peak List Peak Picking Master List ransac algorithm

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Film and television industry cloud exhibition design based on 3D imaging and virtual reality

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DISPLAYS 2021年 70卷

作者： Zhuang, Kaige Dalian Med Univ Art Coll Dalian 116044 Peoples R China

The three-dimensional virtual scene can provide users with a visual three-dimensional virtual environment, with various multimedia channels such as sound, video, force feedback equipment, etc., to bring users a completely immersive interactive experience. This paper introduces 3D imaging and virtual reality technology in the film and television industry cloud exhibition, and develops a virtual display platform. First of all, this paper divides the registration into two processes: camera calibration and joint calibration of the camera and laser scanner based on the calibration results. Camera calibration can determine the plane model of the calibration board in the camera coordinate system, and the joint calibration uses the ransac algorithm to extract the point cloud of the plane model of the calibration board, and then optimizes the distance between the points in the plane model point cloud and the corresponding plane in the camera coordinate system Find the optimal transformation between the two sets of data, and then calculate the registration relationship between the point cloud and the image. Secondly, this article conducts a demand analysis of the film and television industry cloud exhibition platform based on virtual reality technology, including the business goals set by the platform, platform system analysis, overall design, and system operating environment and configuration requirements. This model provides a feasible solution for the visual interaction of the cloud exhibition design of the film and television industry.

关键词： Film and television industry Cloud exhibition 3D imaging Virtual reality ransac algorithm Point cloud matching

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A study on rocker arm defect inspection based on vision system

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INTERNATIONAL JOURNAL OF MODERN PHYSICS B 2024年第12N13期38卷 2440024-2440024页

作者： Nguyen, Thanh-Hung Nguyen, Duc-Toan Tran, Van-Huy Mac, Thi-Thoa Hanoi Univ Sci & Technol Sch Mech Engn 1 Dai Co Viet Rd Hanoi 10000 Vietnam

The rocker arm plays a crucial role in an internal combustion engine's valve train system. Issues often arise when there are errors in the production of the rocker arm, such as the following: (1) misalignment of the rocker arm spindle hole and thread hole;and (2) bevel errors in the rocker arm spindle hole. This paper focuses on the development of a rocker arm chamfering and coaxial defect inspection system, which utilizes the ransac algorithm. The algorithm consists of five steps: (i) representing a 2D point cloud as a matrix with X and Y coordinates;(ii) detecting the number of circles present in the input point cloud;(iii) setting a tolerance threshold for the distance between the selected circle and other points, crucial for achieving high accuracy;(iv) specifying the maximum number of iterations to find the best model from the input points;(v) defining the maximum number of points that can belong to the same circle, considering point density and the anticipated circle's surface. The real-time inspection system is designed with a camera mounted on top of the box, and two LED arrays positioned around the box at suitable distances. Test results using a collected data set demonstrate the effectiveness and accuracy of the proposed method in detecting each type of error. In the experiments, the proposed method successfully detected all coaxial defect samples and achieved a detection rate of 95.1% for chamfer defect samples.

关键词： Rocker arm defect detection ransac algorithm quality control intelligent manufacturing

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A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera

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SENSORS 2016年第10期16卷 1704-1704页

作者： Ci, Wenyan Huang, Yingping Univ Shanghai Sci & Technol Sch Opt Elect & Comp Engn Shanghai 200093 Peoples R China Nanjing Normal Univ Taizhou Colledge Sch Elect Power Engn Taizhou 225300 Peoples R China

Visual odometry estimates the ego-motion of an agent (e.g., vehicle and robot) using image information and is a key component for autonomous vehicles and robotics. This paper proposes a robust and precise method for estimating the 6-DoF ego-motion, using a stereo rig with optical flow analysis. An objective function fitted with a set of feature points is created by establishing the mathematical relationship between optical flow, depth and camera ego-motion parameters through the camera's 3-dimensional motion and planar imaging model. Accordingly, the six motion parameters are computed by minimizing the objective function, using the iterative Levenberg-Marquard method. One of key points for visual odometry is that the feature points selected for the computation should contain inliers as much as possible. In this work, the feature points and their optical flows are initially detected by using the Kanade-Lucas-Tomasi (KLT) algorithm. A circle matching is followed to remove the outliers caused by the mismatching of the KLT algorithm. A space position constraint is imposed to filter out the moving points from the point set detected by the KLT algorithm. The Random Sample Consensus (ransac) algorithm is employed to further refine the feature point set, i.e., to eliminate the effects of outliers. The remaining points are tracked to estimate the ego-motion parameters in the subsequent frames. The approach presented here is tested on real traffic videos and the results prove the robustness and precision of the method.

关键词： visual odometry ego-motion stereovision optical flow ransac algorithm space position constraint

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