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Uniaxial Partitioning Strategy for Efficient point Cloud Registration

SENSORS 2022年第8期22卷 2887页

作者： Souza Neto, Polycarpo Soares, Jose Marques Pereira The, George Andre Univ Fed Ceara Dept Engn Teleinformat BR-60455970 Fortaleza Ceara Brazil

In 3D reconstruction applications, an important issue is the matching of point clouds corresponding to different perspectives of a particular object or scene, which is addressed by the use of variants of the Iterative Closest point (ICP) algorithm. In this work, we introduce a cloud-partitioning strategy for improved registration and compare it to other relevant approaches by using both time and quality of pose correction. Quality is assessed from a rotation metric and also by the root mean square error (RMSE) computed over the points of the source cloud and the corresponding closest ones in the corrected target point cloud. A wide and plural set of experimentation scenarios was used to test the algorithm and assess its generalization, revealing that our cloud-partitioning approach can provide a very good match in both indoor and outdoor scenes, even when the data suffer from noisy measurements or when the data size of the source and target models differ significantly. Furthermore, in most of the scenarios analyzed, registration with the proposed technique was achieved in shorter time than those from the literature.

关键词： 3D point cloud registration partitioning rigid body registration iterative closest point 3D surface matching point matching algorithm

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Coherent point drift peak alignment algorithms using distance and similarity measures for two-dimensional gas chromatography mass spectrometry data

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JOURNAL OF CHEMOMETRICS 2020年第8期34卷 e3236-e3236页

作者： Li, Zeyu Kim, Seongho Zhong, Sikai Zhong, Zichun Kato, Ikuko Zhang, Xiang Wayne State Univ Dept Comp Sci Detroit MI 48202 USA Wayne State Univ Karmanos Canc Inst Biostat Core Detroit MI 48201 USA Wayne State Univ Sch Med Dept Oncol Detroit MI 48201 USA Wayne State Univ Dept Pathol Detroit MI 48201 USA Univ Louisville Dept Chem Louisville KY 40209 USA

The peak alignment is a vital preprocessing step before downstream analysis, such as biomarker discovery and pathway analysis, for two-dimensional gas chromatography mass spectrometry (2DGCMS)-based metabolomics data. Due to uncontrollable experimental conditions, for example, the differences in temperature or pressure, matrix effects on samples, and stationary phase degradation, a shift of retention times among samples inevitably occurs during 2DGCMS experiments, making it difficult to align peaks. Various peak alignment algorithms have been developed to correct retention time shifts for homogeneous, heterogeneous, or both types of mass spectrometry data. However, almost all existing algorithms have been focused on a local alignment and are suffering from low accuracy especially when aligning dense biological data with many peaks. We have developed four global peak alignment (GPA) algorithms using coherent point drift (CPD) point matching algorithms: retention time-based CPD-GPA (RT), prior CPD-GPA (P), mixture CPD-GPA (M), and prior mixture CPD-GPA (P + M). Method RT performs the peak alignment based only on the retention time distance, while methods P, M, and P + M carry out the peak alignment using both the retention time distance and mass spectral similarity. Method P incorporates the mass spectral similarity through prior information, and Methods M and P + M use the mixture distance measure. Four developed algorithms are applied to homogeneous and heterogeneous spiked-in data as well as two real biological data and compared with three existing algorithms, mSPA, SWPA, and BiPACE-2D. The results show that our CPD-GPA algorithms perform better than all existing algorithms in terms of F1 score.

关键词： GC x GC - MS MS similarity peak alignment point matching algorithm

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Global peak alignment for comprehensive two-dimensional gas chromatography mass spectrometry using point matching algorithms

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JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY 2016年第6期14卷 1650032-1650032页

作者： Deng, Beichuan Kim, Seongho Li, Hengguang Heath, Elisabeth Zhang, Xiang Wayne State Univ Dept Math Detroit MI 48201 USA Wayne State Univ Biostat Core Karmanos Canc Inst Detroit MI 48201 USA Wayne State Univ Sch Med Dept Oncol Detroit MI 48201 USA Univ Louisville Dept Chem Louisville KY 46209 USA

Comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC x GC-MS) has been used to analyze multiple samples in a metabolomics study. However, due to some uncontrollable experimental conditions, such as the differences in temperature or pressure, matrix effects on samples and stationary phase degradation, there is always a shift of retention times in the two GC columns between samples. In order to correct the retention time shifts in GC x GC-MS, the peak alignment is a crucial data analysis step to recognize the peaks generated by the same metabolite in different samples. Two approaches have been developed for GC x GC-MS data alignment: profile alignment and peak matching alignment. However, these existing alignment methods are all based on a local alignment, resulting that a peak may not be correctly aligned in a dense chromatographic region where many peaks are present in a small region. False alignment will result in false discovery in the downstream statistical analysis. We, therefore, develop a global comparison-based peak alignment method using point matching algorithm (PMA-PA) for both homogeneous and heterogeneous data. The developed algorithm PMA-PA first extracts feature points (peaks) in the chromatography and then searches globally the matching peaks in the consecutive chromatography by adopting the projection of rigid and nonrigid transformation. PMA-PA is further applied to two real experimental data sets, showing that PMA-PA is a promising peak alignment algorithm for both homogenous and heterogeneous data in terms of F1 score, although it uses only peak location information.

关键词： GC-MS metabolomics peak alignment point matching algorithm

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Advanced weight graph transformation matching algorithm

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IET COMPUTER VISION 2015年第6期9卷 960-966页

作者： Wang, Song Guo, Xin Mu, Xiaomin Huo, Yahong Qi, Lin Zhengzhou Univ Sch Informat Engn Zhengzhou 450001 Henan Peoples R China

An efficient and accurate point matching algorithm named advanced weight graph transformation matching (AWGTM) is proposed in this study. Instead of relying only on the elimination of dubious matches, the method iteratively reserve correspondences which have a small angular distance between two nearest-neighbour graphs. The proposed algorithm is compared against weight graph transformation matching (WGTM) and graph transformation matching (GTM). Experimental results demonstrate the superior performance in eliminating outliers and reserving inliers of AWGTM algorithm under various conditions for images, such as duplication of patterns and non-rigid deformation of objects. An execution time comparison is also presented, where AWGTM shows the best results for high outlier rates.

关键词： graph theory image matching advanced weight graph transformation matching algorithm point matching algorithm AWGTM algorithm iterative correspondence reservation angular distance nearest-neighbour graphs outlier elimination inlier reservation pattern duplication nonrigid object deformation outlier rates

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Low-dose three-dimensional reconstruction of the femur with unit free-form deformation

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MEDICAL PHYSICS 2014年第8期41卷 361-371页

作者： Zeng, Xiangsen Wang, Chentao Zhou, Hai Wei, Shan Chen, Xiaojun Shanghai Jiao Tong Univ Sch Mech Engn Inst Biomed Mfg & Life Qual Engn Shanghai 200240 Peoples R China

Purpose: This paper describes a low-dose method for reconstructing three-dimensional models offemur, using a standard shape model (SSM) and two conventional x-ray images. Methods: The x-ray images were taken in two orthogonal directions. The x-ray source and sensor configurations were documented. An optimized algorithm was employed to align the x-ray image to the three-dimensional model. A method of direct correspondence building is proposed for linking two-dimensional images with three-dimensional projections of a SSM. The reconstruction method proposed in this paper is based on a SSM, which was adapted for x-ray images of individual bones. The adaption was executed by deforming the template bone shape until its silhouette boundary exactly matched the x-ray image of the individual bone. A silhouette-based unit free-form deformation method was evaluated for its suitability in the adaption of the SSM for x-ray images. Comprehensive experiments were designed and conducted for 35 specimens. Results: The validity of the low-dose reconstruction method was demonstrated for the femur, with good results for accuracy (mean error of 1.1 mm, root-mean-square error of 2.1 mm), reproducibility (intraobservation coefficient of variation of 1.1%, interobservation coefficient of variation of 1.4%), and time consumption (mean of 5 min for a full femur). Conclusions: Once this approach has been validated in vivo, it should be suited to multiple applications of routine clinical and research practices. (C) 2014 American Association of Physicists in Medicine.

关键词： low-dose x-ray image point matching algorithm unit free-form deformation three-dimensional reconstruction standard shape model

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Bidirectional Weight Graph Transformation matching algorithm 4

Bidirectional Weight Graph Transformation Matching Algorithm

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International Conference on Audio, Language and Image Processing

作者： Wang, Song Guo, Xin Mu, Xiaomin Qi, Lin Zhengzhou Univ Sch Informat Engn Zhengzhou Peoples R China

ISBN: (纸本)9781479939039

A stable and accurate point matching algorithm named Bidirectional Weight Graph Transformation matching (BWGTM) is proposed in this paper. The algorithm starts with a set of correspondences which contain a variable number of erroneous correspondences, or outliers, in addition to a fixed number of true correspondences (inliers). For each feature point and its K nearest neighbors (KNN), there are two set of graphs to be generated. Depending on the co-angular distances between edges that connect a feature point to its KNN in graphs, the vertices with maximum distance will be founded and deemed as candidate outliers. Considering that some inliers whose KNN consist of outliers are regarded as candidate outliers, a recovery strategy utilizes the addition of fresh vertices to regain these inliers. Experimental results demonstrate the superior performance of this algorithm under various conditions for images.

关键词： point matching algorithm Graph-based algorithm image registration outlier removal

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33rd Chinese Control Conference (CCC)

作者： Mao Min Hao Kuangrong Ding Yongsheng Donghua Univ Coll Informat Sci & Technol Shanghai 201620 Peoples R China Donghua Univ Minist Educ Engn Res Ctr Digitized Text & Fash Technol Shanghai 201620 Peoples R China

ISBN: (纸本)9781479947249

In this paper, a novel point detection method for weak texture is presented. The points with weak texture characteristic are detected by the self-similarity concept. The detection mechanism can be separated into two steps: 1) Detecting the candidate feature points by local self-similarity;2) Using texture strength conception to refine the candidate point set of weak texture. Experiments demonstrate the effectiveness of the proposed point detection algorithm for weak texture.

关键词： Weak texture point matching algorithm point detector Region-similarity

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Bidirectional Weight Graph Transformation matching algorithm

Bidirectional Weight Graph Transformation Matching Algorithm

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International Conference on Audio, Language and Image Processing

作者： Song Wang Xin Guo Xiaomin Mu Lin Qi School of Information Engineering Zhengzhou University

ISBN: (纸本)9781479939046

关键词： point matching algorithm Graph-based algorithm Image registration Outlier removal

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Classification of remote sensing images of fanning areas using resolution fusion algorithm based on optimized point matching

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Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering 2005年第11期21卷 95-98页

作者： Yu, Rong Deng, Xiaolian Wang, Changyao Zhang, Zengxiang Kang, Qing Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China

There are some shortages of traditional image resolution merge algorithm based on point matching, such as huge quantity of calculation, a little low accuracy, and too many restrictions of application. In order to solve these problems, an optimized remote sensing image matching algorithm was introduced in this paper. Moreover, a comparison experiment on traditional and modified image matching algorithm was performed with an ASTER image and a SPOT image. According to the accuracy comparison of classified image, which increased from 81% to 89%, it can be concluded that the modified algorithm is superior to the traditional algorithm, it has much higher accuracy and efficiency than the latter, and it should have more adaptability and applicable value.

关键词： Classification Image fusion point matching algorithm Remote sensing of agriculture

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