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An improved ransac algorithm for 3D wheel alignment

Journal of Measurement Science and Instrumentation 2022年第4期13卷 407-417页

作者： CHENG Wei ZHU Zhifeng YAO Yong WANG Bing ZHOU Fang TANG Dezhi School of Electrical and Information Engineering Anhui University of TechnologyMa’anshan 243000China Anhui FCAR Electronic Technology Co. Ltd.Ma’anshan 243000China

Aiming at the defects of traditional four-wheel aligner such as many sensors,complex operation and slow detection speed,a fast and accurate 3D four-wheel alignment detection method is ***,a new and special circle center target board is designed to calibrate the camera,and then the registration of the homography matrix is optimized by using the improved ransac(Random sample consensus)algorithm combined with the designed special target board,and the parameters of the wheel alignment system are adjusted by using the space vector *** measurements are made to obtain the parameters of the four-wheel *** a calibration comparison experiment between the traditional target board and the new type of target board,and conduct a comparative test with the existing four-wheel aligner of the *** experimental results show that the use of the new target board-binding optimization algorithm can improve the calibration efficiency by about 9%to 21%,while improving the calibration accuracy by about 10.6%to 17.8%.And through the real vehicle test,it is verified that the use of the new target combined with the optimization algorithm can ensure the accuracy and reliability of the four-wheel *** method has a certain significance in the rapid detection of vehicle four-wheel alignment parameters.

关键词： computer vision four-wheel alignment binocular calibration ransac algorithm homography matrix

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Image Stitching for Chest Digital Radiography Using the SIFT and SURF Feature Extraction by ransac algorithm

Image Stitching for Chest Digital Radiography Using the SIFT...

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作者： Siddique Abu Bakar Xiaoming Jiang Xiangfu Gui Guoquan Li Zhangyong Li Information and Communication Engineering Chongqing University of Posts and Telecommunications Biomedical Engineering Chongqing University of Posts and Telecommunications School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Biomedical Engineering Research and Development Chongqing University of Posts and Telecommunications

Image stitching is one of the branches of computer vision. It combines two or more images for a scene to acquire a high-resolution panoramic image. An invariant local function often uses to stitch two images together. Since the flat plate of a digital radiography(DR) system does not cover all parts of the body, the whole bone structure image cannot seize in a single scan. To solved this problem, image stitching is broadly utilized by medical systems to stitch DR images, which can be helpful for scoliosis or lower extremity deformities in the diagnosis, and pre-operative planning are of great importance. In this paper, the stitching and retrieval of medical images planned. To conquer the background noise in medical images, and improve the recovery of quality and stitching rapidity of medical images, a random sample consensus(ransac) algorithm is useful to stitching the images of Chest digital radiography by scaleinvariant feature transform(SIFT) and speeded-up robust features(SURF) feature extraction. Down-sampling utilizes to lessen the size of the images and reduction the measure of calculation. In the interim, the phase correlation is engaged to discover the overlapping region. After feature matching and perspective transformation, the stitched image is gotten dependent on the homography. At last, experimentation has finished showing the presentation.

关键词： Image stitching Chest digital radiograph SIFT and SURF feature extraction ransac algorithm Warp perspective image

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Experimental Study on Instrument Pointer Detection Based on Hough Transform and ransac algorithm 21

Experimental Study on Instrument Pointer Detection Based on ...

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Proceedings of the 2021 4th International Conference on algorithms, Computing and Artificial Intelligence

作者： Minglei Zhao Hongbin Yu Hongyu Shao School of Mechanical Engineering Tianjin Polytechnic University China School of Mechanical Engineering Tianjin University China

ISBN: (纸本)9781450385053

Because of the complex working environment in most factory workshops, the measurement of pointer instrument relies on manual reading. At present, in the field of instrument detection, most algorithms are based on improved image preprocessing and ignore the accuracy, stability and robustness of automatic pointer selection. In order to improve the anti-noise performance of meter pointer selection, ransac (random sampling consistent) algorithm was combined with Hough transform linear detection, and the meter pointer in the binary edge graph was straight-line fitting. The idea of improvement is to use SURF algorithm to extract feature points first and separate points distributed near different lines. Further, ransac algorithm is used to assume the linear model data, given a reasonable inner group, and remove the invalid outlier data. Finally, the Hough transform algorithm is used to fit the instrument pointer line. The linear fitting calibration image verification of the instrument detection pointer shows that the combined algorithm has better fitting effect on the instrument detection pointer, reduces a lot of noise interference and improves the accuracy.

关键词： Instrument testing Computer vision Hough transform ransac algorithm Linear fitting

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Experimental Study on Instrument Pointer Detection Based on Hough Transform and ransac algorithm

Experimental Study on Instrument Pointer Detection Based on ...

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2021年第四届算法、计算和人工智能国际会议

作者： Minglei Zhao Hongbin Yu Hongyu Shao School of Mechanical Engineering Tianjin Polytechnic University School of Mechanical Engineering Tianjin University

Because of the complex working environment in most factory workshops, the measurement of pointer instrument relies on manual reading. At present, in the field of instrument detection, most algorithms are based on improved image preprocessing and ignore the accuracy, stability and robustness of automatic pointer *** order to improve the anti-noise performance of meter pointer selection, ransac(random sampling consistent) algorithm was combined with Hough transform linear detection, and the meter pointer in the binary edge graph was straight-line fitting. The idea of improvement is to use SURF algorithm to extract feature points first and separate points distributed near different lines. Further,ransac algorithm is used to assume the linear model data, given a reasonable inner group, and remove the invalid outlier data. Finally, the Hough transform algorithm is used to fit the instrument pointer line. The linear fitting calibration image verification of the instrument detection pointer shows that the combined algorithm has better fitting effect on the instrument detection pointer, reduces a lot of noise interference and improves the accuracy.

关键词： Hough transform Instrument testing Linear fitting ransac algorithm Computer vision

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An Improved ransac Registration algorithm Based On Region Covariance Descriptor

An Improved RANSAC Registration Algorithm Based On Region Co...

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Chinese Automation Congress (CAC)

作者： Han, Jie Wang, Fei Guo, Yu Zhang, Chuanhao He, Yicong Xi An Jiao Tong Univ Xian Shaanxi Provinc Peoples R China

ISBN: (纸本)9781467371896

Point clouds registration is one of the key parts in 3D model reconstruction. Random Sample Consensus (ransac) is a typical algorithm for coarse registration, which can provide initial values for accurate registration methods such as ICP. In this paper, we propose an improved ransac algorithm based on 3D region covariance descriptor(RC_ransac). Region covariance descriptor of each point in a down sampled point cloud is established. The region covariance descriptor extracts the statistical information of neighborhood for each point. Region covariance descriptor has more significant distinction than Euclidean distance adopted by classical ransac and another improved ransac algorithm, called M_ransac. The accuracy can be improved by significant distinction. Additionally, the region covariance descriptor with compact structure is efficient in time. Experimental results on 3D point clouds registration show that the RC_ransac has superior performance to ransac and M_ransac in computational complexity and accuracy.

关键词： point cloud registration ransac algorithm region covariance descriptor

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Structural Analysis and 3D Reconstruction of Underground Pipeline Systems Based on LiDAR Point Clouds

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REMOTE SENSING 2025年第2期17卷 341-341页

作者： Lai, Qiuyao Xin, Qinchuan Tian, Yuhang Chen, Xiaoyou Li, Yujie Wu, Ruohan Sun Yat Sen Univ Sch Geog & Planning Guangzhou 510275 Peoples R China

The underground pipeline is a critical component of urban water supply and drainage infrastructure. However, the absence of accurate pipe information frequently leads to construction delays and cost overruns, adversely impacting urban management and economic development. To address these challenges, the digital management of underground pipelines has become essential. Despite its importance, research on the structural analysis and reconstruction of underground pipelines remains limited, primarily due to the complexity of underground environments and the technical constraints of LiDAR technology. This study proposes a framework for reconstructing underground pipelines based on unstructured point cloud data, aiming to accurately identify and reconstruct pipe structures from complex scenes. The Random Sample Consensus (ransac) algorithm, enhanced with parameter-adaptive adjustments and subset-independent fitting strategies, is employed to fit centerline segments from the set of center points. These segments were used to reconstruct topological connections, and a Building Information Model (BIM) of the underground pipeline was generated based on the structural analysis. Experiments on actual underground scenes evaluated the method using recall rate, radius error, and deviation between point clouds and models. Results showed an 88.8% recall rate, an average relative radius error below 3%, and a deviation of 3.79 cm, demonstrating the framework's accuracy. This research provides crucial support for pipeline management and planning in smart city development.

关键词： underground pipeline 3D reconstruction point clouds building information model ransac algorithm

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Research on Concentricity Detection Method of Automobile Brake Piston Parts Based on Improved Canny algorithm

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APPLIED SCIENCES-BASEL 2025年第8期15卷 4397-4397页

作者： Li, Qinghua Zhao, Wanting Cheng, Siyuan Ji, Yi Changchun Univ Sch Mech & Vehicle Engn Changchun 130022 Peoples R China

The automotive brake piston component is an important part of the automotive brake system, and the concentricity detection of the first piston component is crucial to ensure driving safety. In this paper, an improved Canny algorithm is proposed for non-contact detection of spring concentricity of the first piston component. Firstly, the traditional Canny algorithm is improved by replacing the Gaussian filter with a bilateral filter to fully retain the edge information, and accurate edge detection results are obtained by constructing a multi-scale analysis. After obtaining the edge images, a sub-pixel edge detection method with gray moments is introduced to optimize these edges;secondly, a circle is fitted to the extracted edge points by using the ransac algorithm to determine the center position and radius of the circle;and finally, the concentricity of the first piston part is calculated based on the fitting results. The experimental results are compared with those of the CMM and the traditional Canny algorithm, and the results show that the improved Canny algorithm reduces the coaxiality error by 4% and enables effective measurement of the concentricity of the first piston assembly spring.

关键词： Canny algorithm bilateral filter multi-scale analysis ransac algorithm concentricity

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Automated Tunnel Point Cloud Segmentation and Extraction Method

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APPLIED SCIENCES-BASEL 2025年第6期15卷 2926-2926页

作者： Wang, Zhe Zhu, Zhenyi Wu, Yong Hong, Qihao Jiang, Donglai Fu, Jinbo Xu, Sifa Zhejiang Univ Technol Coll Civil Engn Hangzhou 310014 Peoples R China Zhejiang Key Lab Intelligent Control Transit Infra Hangzhou 310007 Peoples R China Zhejiang Huadong Surveying & Engn Safety Technol C Hangzhou 311500 Peoples R China

To address the issue of inaccurate tunnel segmentation caused by solely relying on point cloud coordinates, this paper proposes two algorithms, GuSAC and TMatch, along with a ring-based cross-section extraction method to achieve high-precision tunnel lining segmentation and cross-section extraction. GuSAC, based on the ransac algorithm, introduces a minimum spanning tree to reconstruct the topological structure of the tunnel design axis. By using a sliding window, it effectively distinguishes between curved and straight sections of long tunnels while removing non-tunnel structural point clouds with normal vectors, thereby enhancing the lining boundary features and significantly improving the automation level of tunnel processing. At the same time, the TMatch algorithm, which combines cluster analysis and Gaussian Mixture Models (GMMs), achieves accurate segmentation of tunnel rings and inner ring areas and further determines the tunnel cross-section position based on this segmentation result to complete the cross-section extraction. Experimental results show that the proposed method achieves a segmentation accuracy of up to 95% on a standard tunnel point cloud dataset. Compared with traditional centerline extraction methods, the proposed cross-section extraction method does not require complex parameter settings, provides more stable positioning, and demonstrates high practicality and robustness.

关键词： tunnel structure disease analysis ransac algorithm sliding window fitting clustering segmentation Gaussian mixture model scalar field

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Combining SfM and deep learning to construct 3D point cloud models of shield tunnels and Realize spatial localization of water leakages

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MEASUREMENT 2025年 250卷

作者： Qian, Jinhua Xue, Fei Wang, Tianzuo Lin, Zhongqin Cai, Mingcheng Shou, Feifeng Shaoxing Univ Coll Civil Engn Key Lab Rock Mech & Geohazards Zhejiang Prov Shaoxing 312000 Peoples R China Fuzhou Univ Coll Civil Engn Fuzhou 350108 Peoples R China Shaoxing Commun Holding Grp Co Ltd Shaoxing 312000 Peoples R China

To address the inefficiency of traditional 3D reconstruction methods for shield tunnels and their limitations in visualization and leakage localization, this study replaces the dense reconstruction process with the generation of cylindrical point clouds using ransac to extract tunnel contours from SfM-based sparse point clouds. Experiments show that the structural error of the cylindrical point cloud is only 0.47%, and modeling time is reduced by 80.6%. With its uniform and controllable point density, the cylindrical point cloud enables texture mapping through camera parameters, achieving a 190.81% improvement in texture clarity and a 49.4% reduction in overall modeling time compared to traditional methods. Deep learning is further applied for pixel-level leakage segmentation, enabling spatial annotation in the 3D model. This method provides rapid, clear 3D modeling and efficient leakage detection, aiding in spatial leakage analysis.

关键词： 3D reconstruction Shield tunnels Water leakage Leakage detection Water leakage localization ransac algorithm Deep learning

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Comparisons of Planar Detection for Service Robot with ransac and Region Growing algorithm 36

Comparisons of Planar Detection for Service Robot with RANSA...

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第36届中国控制会议

作者： Zhijun Zhang Yongqian Huang Wenkang Zhang Jiawei Luo IEEE The School of Automation Science and Engineering South China University of Technology Pingxiang University

ISBN: (纸本)9781538629185

Considering the life independence of people with disabilities or a limited range of movement,we intend to develop an intelligent mobile service robot equipped with robot manipulator and computer *** order to implement an automatic moving,grasping and delivering task,the abilities of service robot to deal with the images they see and collect useful information are really *** this paper,two different algorithms(i.e.,the ransac algorithm and the region growing algorithm)of the planar detection for the service robot are introduced with detailed principles and implementation *** the foundation of our mobile service robot's development,three specific experiments are designed to compare the algorithms on accuracy,robustness and computational ***,after the comparison between two algorithms,the suitability of two algorithms for the service robot using in the environment detection will be presented and analyzed.

关键词： Service Robot Computer Vision Planar Detection 3D Point Cloud ransac algorithm Region Growing algorithm

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