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Automated detection of boundary line in paddy field using MobileV2-UNet and ransac

COMPUTERS AND ELECTRONICS IN AGRICULTURE 2022年 194卷 106697-106697页

作者： He, Yong Zhang, Xiya Zhang, Zeqing Fang, Hui Zhejiang Univ Coll Biosyst Engn & Food Sci 866 Yuhangtang Rd Hangzhou 310058 Peoples R China Zhejiang Univ Huzhou Inst Hangzhou Peoples R China Zhejiang Univ Huanan Ind Technol Res Inst Guangzhou 510530 Peoples R China

The detection of boundary lines in farmlands is critical for precision agriculture and automatic navigation. This study proposed a novel method for automatic detection of boundary lines in paddy fields based on images acquired from a vision system. These images were collected from different environmental conditions with wheel marks, shadows, weeds, and uneven illumination in paddy fields. To alleviate the effect of this environmental noise on the detection of boundary lines, the proposed method was designed with the required robustness, which included two sequentially linked phases: farmland area segmentation and boundary line detection. For the segmentation of the farmland area, this study proposed an effective deep learning model, called MobileV2-UNet, which used modified inverted residual blocks and the dilated convolution to achieve the accurate segmentation of the farmland area and nonfarmland area. For the detection of farmland boundary lines, a multiboundary detection method based on the frame correlation and random sample consensus (ransac) algorithm was applied to detect the side boundary and end boundary, which could provide critical information for agricultural machinery steering. Results showed that the mean intersection over union (mIoU) for area segmentation reached 0.908, and the average angular and vertical errors for boundary line detection were 0.865 degrees and 0.021, respectively. Moreover, the processing speed reached 8 frames per second, which could meet the real-time work demands of agricultural machinery.

关键词： Visual navigation Semantic segmentation Boundary line detection ransac algorithm

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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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An improved image registration and fusion algorithm

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WIRELESS NETWORKS 2021年第5期27卷 3597-3611页

作者： Li, Dan Chen, Lei Bao, Wenzheng Sun, Jinping Ding, Bin Li, Zilong Xuzhou Univ Technol Informat & Elect Engn Coll Key Lab Intelligent Ind Control Technol Jiangsu P Xuzhou 221000 Jiangsu Peoples R China

Under the background of telemedicine, a new registration and mosaic algorithm for medical images is proposed in this paper to solve the problems of electronic noise, uneven illumination and ray scattering in the real-time medical process. The improved Retinex algorithm by trilateral filter and homomorphic filtering algorithm can enhance the image effectively in preprocessing. The improved phase correlation algorithm based on log polar transformation was used to calculate parameters, such as rotation, scaling and translation. Then, the SUSAN corner matching points were extracted in overlapping positions, the improved KD tree was used for enhancing matching efficiency. Later, matching points were purified by the improved ransac algorithm. Finally, images were processed by Laplacian pyramid decomposition algorithm to make the image joint seemed smooth and natural. The results of experiments and evaluation criteria confirm that the new method has high robustness in the process of medical image registration and stitching in the network.

关键词： Logarithmic polar coordinates Retinex algorithm ransac algorithm Laplacian pyramid decomposition

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Applying image registration algorithm combined with CNN model to video image stitching

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JOURNAL OF SUPERCOMPUTING 2021年第12期77卷 13879-13896页

作者： Cao, Weiran Zhejiang Yuexiu Univ Coll Network Commun Shaoxing Peoples R China Sangmyung Univ Coll Design Seoul South Korea

The purposes are to explore the video image stitching technique of Unmanned Aerial Vehicles (UAVs), expand the application of image registration algorithms and new sensing equipment in video image stitching, and improve the development of video remote sensing image processing. First, how to remotely stitch UAV video images is analyzed. Second, the Scale Invariant Feature Transform (SIFT) algorithm is improved by re-dividing the pixel region and incorporating the vector correlation coefficient. Then, the matching results of the improved SIFT algorithm are compared with those of the traditional SIFT algorithm and Speed Up Robust Feature algorithm. Second, the Random Sample Consensus algorithm is introduced to match the video images accurately, and the matching accuracy of the converted images is verified. Finally, the improved image registration algorithm, the homography matrix estimation model based on convolutional neural network, and the conformation equation of the video sensor are combined to complete the video image stitching of UAVs. Also, the stitching quality of the video image is analyzed. The results show that the improved SIFT algorithm is better than the traditional SIFT algorithm in terms of correct matching and matching time. The visually transformed finely-matched image has a higher matching accuracy rate, and the combination of the two registration algorithms eliminates mismatch points effectively. Compared with the traditional stitching method, the video image stitching method proposed in this study has a higher structural similarity index and edge difference spectrum index, which is feasible and effective. The combination of image registration algorithm with new sensors and deep learning has great application potential in video image stitching.

关键词： SIFT algorithm UAV Video image stitching Large plane array video sensor Convolutional neural network ransac algorithm Fine image stitching

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Comparison of estimation algorithms for individual tree diameter at breast height based on hand-held mobile laser scanning

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SCANDINAVIAN JOURNAL OF FOREST RESEARCH 2021年第6期36卷 460-473页

作者： Fan, Weiwei Liu, Haoran Xu, Yongsheng Lin, Wenshu Northeast Forestry Univ Coll Engn & Technol Harbin 150040 Peoples R China

Hand-held mobile laser scanning (HMLS) can quickly and effectively obtain tree point cloud data, which has great potential to conduct forest resource survey at the plot or stand scale. To improve the estimation precision of Diameter at Breast Height (DBH) for individual trees based on HMLS data, four algorithms were compared and the ideal conditions (slice thickness, inclination, point cloud integrity) of use for each algorithm were evaluated. First, the original point cloud data were denoised, sliced, layered, and clustered based on the normalized point cloud data. Then, the tree DBH was estimated by the four algorithms under different conditions. Results showed that: (1) The optimal point cloud thickness for estimating tree DBH was 5 cm for the two-dimensional algorithms and 15 cm for the three-dimensional algorithm. (2) The root mean square error (RMSE) varied by approximately 0.5 and 0.18 cm with the change of inclination for two-dimensional algorithms and three-dimensional algorithm, respectively. (3) A reduction in point cloud integrity can affect the accuracy of all four algorithms, while the fast convex hull algorithm was the most impacted. The two-dimensional algorithms were computationally more efficient than the three-dimensional one. However, the former was less robust than the latter.

关键词： Handheld mobile laser scanning DBH Hough transform algorithm fast convex hull algorithm ransac algorithm nonlinear least-squares cylindrical-fitting algorithm

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Identification and reading method of pointer meter based on CBAM D2-Net 19

Identification and reading method of pointer meter based on ...

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19th IEEE International Conference on Mechatronics and Automation (IEEE ICMA)

作者： Liu, Hongli Shen, Qingyang Shao, Lei Li, Ji Tianjin Univ Technol Sch Elect Engn & Automat Tiahlin Key Lab Control Theory & Applicat Complic Binshui Xidao 391 Tianjin Peoples R China

ISBN: (数字)9781665408530

ISBN: (纸本)9781665408530;9781665408523

In order to read the ambiguous and reflective pointer instruments collected on site, a D2-net model based on CBAM is proposed, and an attention mechanism is introduced into the feature extraction network to focus the feature point detection on the salient part to capture more It has a good visual structure, and takes the angle method as the core, and uses the ransac algorithm to fit the angle of the instrument for interpretation. Experiments show that the accuracy of the instrument identification and interpretation method in this paper is within the allowable error range in all cases, and the registration and reading of all samples are successful, and there is no obvious fluctuation in reflective interference and image blurring. The comparison shows that for the highest stability.

关键词： CBAM D2 net pointer meter image registration ransac algorithm

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Research on Detection Technology of Micro-Components on Circuit Board Based on Digital Image Processing

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Journal of Electronic Research and Application 2024年第3期8卷 230-233页

作者： Aibin Tang Yi Liu Chunyin Liu Libin Yang Department of Information Science and Engineering Hunan University of HumanitiesScience and TechnologyLoudi 417000China Hunan Xiangdian Test and Research Institute Co. LTD.Changsha 410000China

Aiming at the stability of the circuit board image in the acquisition process,this paper realizes the accurate registration of the image to be registered and the standard image based on the SIFT feature operator and ransac *** device detection model and data set are established based on Faster ***,the number of training was continuously optimized,and when the loss function of Faster RCNN converged,the identification result of the device was obtained.

关键词： Tiny device recognition Image registration SIFT feature operator ransac algorithm Faster RCN

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Point cloud voxel classification of aerial urban LiDAR using voxel attributes and random forest approach

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INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 2023年 118卷

作者： Aljumaily, Harith Laefer, Debra F. Cuadra, Dolores Velasco, Manuel Carlos III Univ Madrid Dept Comp Sci & Engn Ave Univ 30 Madrid 28911 Spain NYU Ctr Urban Sci & Progress Tandon Sch Engn 370 Jay St Brooklyn NY 11201 USA NYU Tandon Sch Engn Dept Civil & Urban Engn 370 Jay St Brooklyn NY 11201 USA King Juan Carlos Univ Dept Comp Sci & Stat Madrid Spain

The opportunities now afforded by increasingly available, dense, aerial urban LiDAR point clouds (greater than100 pts/m2) are arguably stymied by their sheer size, which precludes the effective use of many tools designed for point cloud data mining and classification. This paper introduces the point cloud voxel classification (PCVC) method, an automated, two-step solution for classifying terabytes of data without overwhelming the computational infrastructure. First, the point cloud is voxelized to reduce the number of points needed to be processed sequentially. Next, descriptive voxel attributes are assigned to aid in further classification. These attributes describe the point distribution within each voxel and the voxel's geo-location. These include 5 pointdescriptors (density, standard deviation, clustered points, fitted plane, and plane's angle) and 2 voxel position attributes (elevation and neighbors). A random forest algorithm is then used for final classification of the object within each voxel using four categories: ground, roof, wall, and vegetation. The proposed approach was evaluated using a 297,126,417 point dataset from a 1 km2 area in Dublin, Ireland and 50% denser dataset of New York City of 13,912,692 points (150 m2). PCVC's main advantage is scalability achieved through a 99 % reduction in the number of points that needed to be sequentially categorized. Additionally, PCVC demonstrated strong classification results (precision of 0.92, recall of 0.91, and F1-score of 0.92) compared to previous work on the same data set (precision of 0.82-0.91, recall 0.86-0.89, and F1-score of 0.85-0.90).

关键词： Object Classification MapReduce Big Data LiDAR DBSCAN algorithm ransac algorithm

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

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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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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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