• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.401-410
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• 2016

3D registration is a computer vision technique of aligning multi-view range images with respect to a reference coordinate system. Various 3D registration algorithms have been introduced in the past few decades. Iterative Closest Point (ICP) is one of the widely used 3D registration algorithms, where various modifications are available nowadays. In the ICP-based algorithms, the closest points are considered as the corresponding points. However, this assumption fails to find matching points accurately when the initial pose between point clouds is not sufficiently close. In this paper, we propose a new method to solve this problem using the 6D distance (3D color space and 3D Euclidean distances). Moreover, a color segmentation-based adaptive sampling technique is used to reduce the computational time and improve the registration accuracy. Several experiments are performed to evaluate the proposed method. Experimental results show that the proposed method yields better performance compared to the conventional methods.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.601-606
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• 1999

A Walsh function method is proposed in this report for the analysis and optimal control of linear time-delay systems, which is based on the Picard's iterative approximation and fast Walsh transformation. In this research, the following results are obtained: 1) The differential and integral equation can be solved by transforming into a simple algebraic equation as it was possible with the usual orthogonal function method: 2) General orthogonal function methods require usage of Walsh operational matrices for delay or advance and many calculations of inverse matrices, which are not necessary in this method. Thus, the control problems of linear time-delay systems can be solved much faster and readily.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4463-4482
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• 2020

Mesh model generated from 3D reconstruction usually comes with lots of noise, which challenges the performance and robustness of mesh simplification approaches. To overcome this problem, we present a novel method for mesh simplification which could preserve structure and improve the accuracy. Our algorithm considers both the planar structures and linear features. In the preprocessing step, it automatically detects a set of planar structures through an iterative diffusion approach based on Region Seed Growing algorithm; then robust linear features of the mesh model are extracted by exploiting image information and planar structures jointly; finally we simplify the mesh model with plane constraint QEM and linear feature preserving strategies. The proposed method can overcome the known problem that current simplification methods usually degrade the structural characteristics, especially when the decimation is extreme. Our experimental results demonstrate that the proposed method, compared to other simplification algorithms, can effectively improve the quality of mesh and yield an increased robustness on noisy input mesh.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.347-370
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• 2019

In the computer-aided detection (CAD) system of pulmonary nodules, a high false positive rate is common because the density and the computed tomography (CT) values of the vessel and the nodule in the CT images are similar, which affects the detection accuracy of pulmonary nodules. In this paper, a method of automatic detection of pulmonary nodules based on multi-scale enhancement filters and 3D shape features is proposed. The method uses an iterative threshold and a region growing algorithm to segment lung parenchyma. Two types of multi-scale enhancement filters are constructed to enhance the images of nodules and blood vessels in 3D lung images, and most of the blood vessel images in the nodular images are removed to obtain a suspected nodule image. An 18 neighborhood region growing algorithm is then used to extract the lung nodules. A new pulmonary nodules feature descriptor is proposed, and the features of the suspected nodules are extracted. A support vector machine (SVM) classifier is used to classify the pulmonary nodules. The experimental results show that our method can effectively detect pulmonary nodules and reduce false positive rates, and the feature descriptor proposed in this paper is valid which can be used to distinguish between nodules and blood vessels.

• Journal of applied mathematics & informatics
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• v.29 no.1_2
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• pp.227-245
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• 2011

In this paper, we introduce a new iterative method for finding a common element of the set of solutions for mixed equilibrium problem, the set of solutions of the variational inequality for a ${\beta}$inverse-strongly monotone mapping and the set of fixed points of a family of finitely nonexpansive mappings in a real Hilbert space by using the viscosity and Ces$\`{a}$ro mean approximation method. We prove that the sequence converges strongly to a common element of the above three sets under some mind conditions. Our results improve and extend the corresponding results of Kumam and Katchang [A viscosity of extragradient approximation method for finding equilibrium problems, variational inequalities and fixed point problems for nonexpansive mapping, Nonlinear Analysis: Hybrid Systems, 3(2009), 475-86], Peng and Yao [Strong convergence theorems of iterative scheme based on the extragradient method for mixed equilibrium problems and fixed point problems, Mathematical and Computer Modelling, 49(2009), 1816-828], Shimizu and Takahashi [Strong convergence to common fixed points of families of nonexpansive mappings, Journal of Mathematical Analysis and Applications, 211(1) (1997), 71-83] and some authors.

• Journal of Communications and Networks
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• v.14 no.1
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• pp.21-26
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• 2012

As electrocardiogram (ECG) signals are generally sampled with a frequency of over 200 Hz, a method to compress diagnostic information without losing data is required to store and transmit them efficiently on a wireless personal area network (WPAN). In this paper, an ECG signal compression method for communications onWPAN, which uses feature points based on curvature, is proposed. The feature points of P, Q, R, S, and T waves, which are critical components of the ECG signal, have large curvature values compared to other vertexes. Thus, these vertexes were extracted with the proposed method, which uses local extrema of curvatures. Furthermore, in order to minimize reconstruction errors of the ECG signal, extra vertexes were added according to the iterative vertex selectionmethod. Through the experimental results on the ECG signals from Massachusetts Institute of Technology-Beth Israel hospital arrhythmia database, it was concluded that the vertexes selected by the proposed method preserved all feature points of the ECG signals. In addition, it was more efficient than the amplitude zone time epoch coding method.

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.1
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• pp.17-27
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• 2004

A new earthquake design method performing iterative calculations using secant stiffness was developed. The proposed design method has the advantages of convenience and stability in numerical analysis because it uses elastic analysis. At the same time, the proposed design method can accurately estimate the strength and ductility demands on the members because it performs the analysis on the inelastic behavior of structure using iterative calculation. In the present study, the procedure of the proposed design method was established, and a computer program incorporating the proposed method was developed. Design examples using the proposed method were presented, and its advantages were presented by the comparisons with existing design methods using elastic or inelastic analysis. The proposed design method, as an integrated method of analysis and design, can address the earthquake design strategy devised by the engineer. such as ductility limit on each member, the design concept of strong column - weak beam, and etc. In addition, through iterative calculations on the structure preliminarily designed only with member sizing, the strength and ductility demands of each member can be directly calculated so as to satisfy the given design strategy. As the result. economical and safe design can be achieved.

• Journal of Biomedical Engineering Research
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• v.30 no.1
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• pp.34-40
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• 2009

Transforms including translation and rotation are required for registering two or more images. In medical applications, different registration methods have been applied depending on the structures: for rigid bodies such as bone structures, affine transformation was widely used. In most previous research, a single transform was used for registering the whole images, which resulted in low registration accuracy especially when the degree of deformation was high between two images. In this paper, a novel registration method is introduced which is based image sub-division and bilinear interpolation of transformations. The proposed method enhanced the registration accuracy by 40% comparing with Trimmed ICP for registering color and MRI images.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.247-252
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• 2004

In this paper are proposed 2nd-order PD-type iterative learning control algorithms for linear continuous-time system and linear discrete-time system. In contrast to conventional methods, the proposed learning algorithms are constructed based on both time-domain performance and iteration-domain performance. The convergence of the proposed learning algorithms is proved. Also, it is shown that the proposed method has robustness in the presence of external disturbances and the convergence accuracy can be improved. A numerical example is provided to show the effectiveness of the proposed algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.355-363
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• 2011

Recently, as one of several methods to improve the performance of DVC(Distributed Video Coding) system, many research works are focusing on the iterative refinement of side information. Most of the conventional techniques are mainly based on the relationship between the reconstruction level and side information, or the vector median filtering of motion vectors, but, their performance improvements are restricted. In order to overcome the performance limit of the conventional schemes, in this paper, a side information generation scheme is designed by measuring the block-cost estimation. Then, by adaptively selecting the compensation mode using the received bit-plane information, we propose a block-adaptive iterative refinement which is efficient for non-symmetric moving objects. Computer simulations show that, by using the proposed refinement method, the performance can be improved up to 0.2 dB in rate-distortion.