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Affine iterative closest point algorithm for point set registration

PATTERN RECOGNITION LETTERS 2010年第9期31卷 791-799页

作者： Du, Shaoyi Zheng, Nanning Ying, Shihui Liu, Jianyi Xi An Jiao Tong Univ Inst Artificial Intelligence & Robot Xian 710049 Peoples R China Shanghai Univ Sch Sci Dept Math Shanghai 200444 Peoples R China

The traditional iterative closest point (ICP) algorithm is accurate and fast for rigid point set registration but it is unable to handle affine case. This paper instead introduces a novel generalized ICP algorithm based on lie group for affine registration of m-D point sets. First, with singular value decomposition technique applied, this paper decomposes affine transformation into three special matrices which are then constrained. Then, these matrices are expressed by exponential mappings of lie group and their Taylor approximations at each iterative step of affine ICP algorithm. In this way, affine registration problem is ultimately simplified to a quadratic programming problem. By solving this quadratic problem, the new algorithm converges monotonically to a local minimum from any given initial parameters. Hence, to reach desired minimum, good initial parameters and constraints are required which are successfully estimated by independent component analysis. This new algorithm is independent of shape representation and feature extraction, and thereby it is a general framework for affine registration of m-D point sets. Experimental results demonstrate its robustness and efficiency compared with the traditional ICP algorithm and the state-of-the-art methods. (c) 2010 Elsevier B.V. All rights reserved.

关键词： Affine point set registration iterative closest point algorithm Lie group Singular value decomposition Independent component analysis

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Registration of Micro-Computed Tomography and Histological Images of the Guinea Pig Cochlea to Construct an Ear Model Using an iterative closest point algorithm

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ANNALS OF BIOMEDICAL ENGINEERING 2010年第5期38卷 1719-1727页

作者： Lee, Chia-Fone Li, Gen-Jia Wan, Shu-Yen Lee, Wen-Jeng Tzen, Kai-Yuan Chen, Chiung-Hsiang Song, Yu-Lin Chou, Yuan-Fang Chen, Yuh-Shyang Liu, Tien-Chen Tai Tung Christian Hosp Dept Otolaryngol Tai Tung 950 Taiwan Natl Taiwan Univ Hosp Dept Otolaryngol Taipei 100 Taiwan Tzu Chi Gen Hosp Dept Otolaryngol Hualien 970 Taiwan Tzu Chi Univ Dept Med Hualien 970 Taiwan Chang Gung Univ Dept Informat Management Tao Yuan 333 Taiwan Natl Taiwan Univ Dept Elect Engn Taipei 790 Taiwan Natl Taiwan Univ Hosp Dept Med Imaging Taipei 100 Taiwan Natl Taiwan Univ Hosp Dept Nucl Med Taipei 100 Taiwan Natl Taiwan Univ Neurobiol & Cognit Sci Ctr Taipei 790 Taiwan Natl Taiwan Univ Sch Vet Med Taipei 790 Taiwan Natl Taiwan Univ Dept Mech Engn Taipei 790 Taiwan

We present a practical and systematic method to reconstruct accurate physical models of the guinea pig ear (n = 1). The method uses a semi-automatic technique to create three-dimensional (3-D) models of the guinea pig cochlea by registration of micro-computed tomography (CT) and histological images. An iterative closest point algorithm was employed to minimize the sum of square errors with respect to the closest histological model and corresponding micro-CT model. This allowed creation of an accurate geometric ear model including external ear canal, tympanic membrane, middle ear cavity, auditory ossicles, and the cochlea. The characteristic cross-sectional areas of scala tympani, scala vestibuli, and scala media were measured. The length, thickness, and apex width of the guinea pig's basilar membrane were compared to the data found in literature. Some shape parameters were also compared among different species. The results confirmed that the geometric model created by this method was accurate. This method provides an effective way to visualize the 3-D structure and the detailed information about ear geometry required for finite element and multibody dynamic analysis.

关键词： Ear Image reconstruction iterative closest point algorithm 3-D model

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A Novel Radiologic Assessment of Screw Loosening Focusing on Spatial Position Change of Screws Using an iterative closest point algorithm with Stereolithography Data: Technical Note

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WORLD NEUROSURGERY 2019年 124卷 171-177页

作者： Tanioka, Satoru Ishida, Fujimaro Kuraishi, Keita Tanaka, Katsuhiro Shimosaka, Shinichi Suzuki, Hidenori Mizuno, Masaki Mie Chuo Med Ctr Dept Neurosurg Tsu Mie Japan Mie Univ Dept Neurosurg Grad Sch Med Tsu Mie Japan

OBJECTIVE: In thoracolumbar spinal instrumentation surgery, pedicle screw fixation is widely used, whereas screw loosening occurs only occasionally over time. It is common to evaluate screw loosening by the radiographic lucent zone around screws, which can neither evaluate loosening quantitatively nor detect slight screw loosening. In the present technical note, we describe a novel assessment technique of screw loosening by generating 3-dimensional screw images from computed tomography data and superposing them in time series. METHODS: Computed tomography data were exported in digital imaging and communications in medicine dataset and imported to the 3-dimensional computer-aided designing software, by which screws and rods were segmented and outputted in stereolithography (STL) format. The STL files were imported to the software, and registration based on iterative closest point algorithm was performed to assess screw position changes. RESULTS: Positional changes on STL in time series were classified into 3 types: 1) no position changes existed in the entire system of screws and rods;2) position changes existed in the entire system of screws and rods, but no position changes were shown when the left-sided and right-sided screws and rod were separately evaluated;and 3) position changes existed in the left and/or right-sided screws and rods even when evaluated separately. CONCLUSIONS: This technique enables the quantitative evaluation of screw loosening and loosening between screws and rods. In conjunction with conventional methods of assessing radiographic lucent zone, we are able to obtain more accurate information regarding screw loosening after spinal instrumentation surgery.

关键词： iterative closest point algorithm Screw loosening Spatial position change of screws Spinal instrumentation surgery Stereolithography

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Morphological iterative closest point algorithm

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IEEE TRANSACTIONS ON IMAGE PROCESSING 1999年第11期8卷 1644-1646页

作者： Kapoutsis, CA Vavoulidis, CP Pitas, I Aristotelian Univ Salonika Dept Informat GR-54006 Salonika Greece

This work presents a method for the registration of three-dimensional (3-D) shapes. The method is based on the iterative closest point (ICP) algorithm and improves it through the use of a 3-D volume containing the shapes to be registered. The Voronoi diagram of the "model" shape points is first constructed in the volume. Then this is used for the calculation of the closest point operator. This way a dramatic decrease of the computational cost is achieved.

关键词： iterative closest point algorithm Voronoi tesselation

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Adaptive hill climbing and iterative closest point algorithm for multisensor image registration with partial Hausdorff distance

Adaptive hill climbing and iterative closest point algorithm...

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Conference on Sensor Fusion: Architectures, algorithms, and Applications IV

作者： Yang, XJ Sheng, YL Guan, WG Valin, P Sévigny, L Univ Laval Dept Phys Ctr Opt Photon & Laser Image Sci Grp St Foy PQ G1K 7P4 Canada

ISBN: (纸本)0819436771

Challenge in the registration of battlefield images in visible and far-infrared bands is the feature inconsistency. We propose a contour-based approach for the registration and apply two free-form curve-matching algorithms: adaptive hill climbing and the iterative closest point algorithm. Both algorithms do not requires explicit curve feature correspondence, are designed to be robust against outliers. We formulate the search as an adaptive hill climbing optimization for minimizing the partial Hausdorff distances. In the iterative closest point algorithm we choose the mean partial distance as the objective function, so that outliers can be easily handled by using rank order statistics.

关键词： free-form curve matching Hausdorff distance hill climbing optimization iterative closest point algorithm

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THREE-DIMENSIONAL point-CLOUD REGISTRATION USING A GENETIC algorithm AND THE iterative closest point algorithm

THREE-DIMENSIONAL POINT-CLOUD REGISTRATION USING A GENETIC A...

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International Conference on Evolutionary Computation Theory and Applications (ECTA 2011) / International Conference on Fuzzy Computation Theory and Applications (FCTA 2011)

作者： Torres, D. Cuevas, F. J. Ctr Invest Opt AC Comp Vis & Artificial Intelligence Grp Loma del Bosque 115 Lomas Del Campestre 37150 Leon Mexico

ISBN: (纸本)9789898425836

We present a method for three-dimensional surface registration which utilizes a Genetic algorithm (GA) to perform a coarse alignment of two scattered point clouds followed by a slight variation of the iterative closest point (ICP) algorithm for a final fine-tuning. In this work, in order to improve the time of convergence, a sampling method consisting of three steps is used: 1) sample over the geometry of the clouds based on a gradient function to remove easily interpolating singularities;2) a random sampling of the clouds and 3) a final sampling based on the overlapping areas between the clouds. The presented method requires no more than 25% of overlapping surface between the two scattered point clouds and no rotational or translational information is needed. The proposed algorithm has shown a good convergence ratio with few generations and usability through automated applications such as object digitalization and reverse engineering.

关键词： point-cloud registration Evolutionary computation Genetic algorithm iterative closest point algorithm

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Robust Scale iterative closest point algorithm Based on Correntropy for point Set Registration

Robust Scale Iterative Closest Point Algorithm Based on Corr...

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Australian Control Conference (AuCC)

作者： Chen, Hongchen Wu, Zongze Du, Shaoyi Zhou, Nan Sun, Jing South China Univ Technol Sch Elect & Informat Engn Guangzhou 510000 Guangdong Peoples R China Xi An Jiao Tong Univ Inst Artificial Intelligence & Robot Xian 710049 Peoples R China Univ Elect Sci & Technol China Sch Automat Engn Chengdu 611731 Peoples R China Guangdong Univ Technol Sch Automat Guangzhou 510006 Guangdong Peoples R China

ISBN: (纸本)9781922107909

point set registration is important for calibration of multiple cameras, 3D reconstruction and recognition, etc. The traditional scale iterative closest point (ICP) algorithm is fast and accurate for scale registration of point sets, but it performs worse when the point sets with large outliers or noise. This paper introduces a novel algorithm based on correntropy for scale registration of noisy point sets. Firstly, the definition of correntropy is introduced and its property of eliminating outliers is demonstrated by comparing with the mean square error (MSE). Secondly, a novel objective function of scale registration problem is proposed by applying the maximum correntropy criterion (MCC). After that, a new scale ICP algorithm is proposed to solve this energy function. This method uses a simple iterative algorithm and computes the scale transformation by methods including half-quadratic technique and derivation quickly at each iterative step. Similar to the ICP algorithm, this new algorithm converges monotonically to a local maximum for any given initial parameters. Experimental results demonstrate that our algorithm has the high speed and accuracy for scale registration with outliers compared with the traditional scale ICP algorithm and the state-of-the-art algorithms.

关键词： iterative closest point algorithm Robustness Linear programming Kernel Random variables Optimization Australia Set of points Random variable Mean square error outliers iterative closest point algorithm Registration linear programming Inductively coupled plasma Robustness Scale formation Kernel

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The parallel iterative closest point algorithm 3

The parallel iterative closest point algorithm

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3rd International Conference on 3-D Digital Imaging and Modeling

作者： Langis, C Greenspan, M Godin, G Natl Res Council Canada Inst Informat Technol Visual Informat Technol Grp Ottawa ON K1A 0R6 Canada

ISBN: (纸本)0769509851

This paper describes a parallel implementation developed to improve the time performance of the iterative closest point algorithm. Within each iteration, the correspondence calculations are distributed among the processor resources. Ar the end of each iteration, the results of the correspondence determination are communicated back to a central processor and the current transformation is calculated A number of additional techniques were developed that sen,ed to improve upon this basic scheme. Calculating the partial sums within each distributed resource made it unnecessary to transmit the correspondence values back to the central processor, which reduced the communication overhead, and improved time performance. Randomly distributing the points among the processor resources resulted in a better load balancing, which further improved time performance. We also found that thinning the image by randomly removing a certain percentage of the points did not improve the performance, when viewed as the progression of mse with time. The method was implemented and tested on a 22 node Beowulf class cluster. For a large image, linear performance improvements were obtained for up to 16 processors, while they held for rtp to 8 processors with a smaller image.

关键词： Councils Data acquisition Data processing Information technology Inspection iterative closest point algorithm Load management Mean square error methods Registers Testing

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Surface-based 3-D image registration using the iterative closest point algorithm with a closest point transform

Surface-based 3-D image registration using the Iterative Clo...

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Conference on Image Processing - Medical Imaging 1996

作者： Ge, YR Maurer, CR Fitzpatrick, JM WAKE FOREST UNIV BOWMAN GRAY SCH MEDDEPT RADIOLDEPT MATH & COMP SCIWINSTON SALEMNC 27109

ISBN: (纸本)0819420859

Image registration is a valuable technique for medical diagnosis and treatment. It allows physicians to combine information from multiple images by aligning them into the same coordinate space. Surface-based methods register images by aligning corresponding surfaces of one or more anatomical structures such as the surface of the brain or skull. In this paper we examine a novel implementation of this approach. We use the iterative closest point algorithm to iteratively search for the transformation that minimizes the distance between surface points in one image and a surface model in the other image. In each iteration we use the closest point transform to find corresponding points that are closest with respect to the transformation estimated in the previous iteration. Results from several experiments are presented to demonstrate the efficacy of this approach.

关键词： image registration surface-based registration iterative closest point algorithm distance transform closest point transform

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Improved iterative closest point algorithm using Truncated Signed Distance Function 18

Improved Iterative Closest Point Algorithm using Truncated S...

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18th International Conference on Control, Automation and Systems (ICCAS)

作者： Kim, Hanjun Hong, H. K. Lee, B. H. Seoul Natl Univ Dept Elect & Comp Engn ASRI Seoul 08826 South Korea

ISBN: (纸本)9788993215151

Truncated signed distance is one of the methods to represent 3D spatial information by using the distance from the surface of an object, and is mainly used for 3D dense reconstruction. When using truncated signed distance value for 3D reconstruction, iterative closest point algorithm is generally used for matching two point clouds. However, iterative closest point algorithm for 3D reconstruction uses only the geometric information of point clouds themselves. Due to lack of information in the surface structure, it is possible to fall in the local minimum or occur convergence failure in iteration process. To solve these problems, we use additional information from truncated signed distance function values. As we optimize the joint objective function composed of the geometric information and the truncated signed distance function information, it is possible to register two point clouds to be more robust in iterative closest point algorithm. Experimental results demonstrate that the proposed method outperforms the conventional method using only a geometric information.

关键词： iterative closest point algorithm truncated signed distance function 3D reconstruction 3D registration

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