• 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.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.891-894
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• 1999

ICP reactor produces high-density and high-uniformity plasma in large area, are has excellent characteristic of direction in the case of etching. Until now, many algorithms used one mesh method. These algorithms are not appropriate for sub 0.1 ${\mu}{\textrm}{m}$ device technologies which should deal with each ion. These algorithms could not present exactly straggle and interaction between projectile ions and could not consider reflection effects due to interactions among next projectile ions, reflected ions and sputtering ions, simultaneously. And difficult consider am-bipolar drift effect.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.942-945
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• 1999

In this work, we proposed Proper etching algorithm for ultra-large scale integrated circuit device and simulated etching process using the proposed algorithm in the case of ICP (inductive coupled plasma) 〔1〕source. Until now, many algorithms for etching process simulation have been proposed such as Cell remove algorithm, String algorithm and Ray algorithm. These algorithms have several drawbacks due to analytic function; these algorithms are not appropriate for sub 0.1 ${\mu}{\textrm}{m}$ device technologies which should deal with each ion. These algorithms could not present exactly straggle and interaction between Projectile ions and could not consider reflection effects due to interactions among next projectile ions, reflected ions and sputtering ions, simultaneously In order to apply ULSI process simulation, algorithm considering above mentioned interactions at the same time is needed. Proposed algorithm calculates interactions both in plasma source region and in target material region, and uses BCA (binary collision approximation4〕method when ion impact on target material surface. Proposed algorithm considers the interaction between source ions in sheath region (from Quartz region to substrate region). After the collision between target and ion, reflected ion collides next projectile ion or sputtered atoms. In ICP etching, because the main mechanism is sputtering, both SiO$_2$ and Si can be etched. Therefore, to obtain etching profiles, mask thickness and mask composition must be considered. Since we consider both SiO$_2$ etching and Si etching, it is possible to predict the thickness of SiO$_2$ for etching of ULSI.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.12
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• pp.525-530
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• 2022

Although the iterative closest point (ICP) algorithm has been widely used to align two point clouds, ICP tends to fail when the initial orientation of the two point clouds are significantly different. In this paper, when two triangular meshes A and B have significantly different initial orientations, we present an algorithm to align them. After obtaining weighted centroids for meshes A and B, respectively, vertices that are likely to correspond to each other between meshes are set as feature points using the distance from the centroid to the vertices. After rotating mesh B so that the feature points of A and B to be close each other, RMSD (root mean square deviation) is measured for the vertices of A and B. Aligned meshes are obtained by repeating the same process while changing the feature points until the RMSD is less than the reference value. Through experiments, we show that the proposed algorithm aligns the mesh even when the ICP and Go-ICP algorithms fail.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.281-287
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• 2010

This study compares transformation algorithms for co-registration of terrestrial laser scan data. Pair-wise transformation which is used for transformation of scan data from more than two different view accumulates errors. ICP algorithm commonly used for co-registration between scan data needs initial geometry information. And it is difficult to co-register simultaneously because of too many control points when managing scan at the same time. Therefore, this study perform global registration technique using matching points. Matching points are extracted automatically from intensity image by SIFT and global registration is performed using GP analysis. There are advantages for operation speed, accuracy, automation in suggested global registration algorithm. Through the result from it, registration algorithms can be developed by considering accuracy and speed.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.10 s.175
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• pp.107-113
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• 2005

This paper presents a method to reduce errors in registration, which is used in transformation coordinate system of the multiple measuring data. In general, the ICP algorithms and feature-based approaches are used for registration. In order to measure wrap-around object, it is necessary to change the scanning direction or set-up of the object. A fixture is made to reduce registration errors caused by inaccurate center point of tooling balls, providing the more accurate registration method. And, the motorized fixture controls rotation and tilting to get precise the measuring data and registration. The proposed motorized fixture and registration method have advantages in accurate registration and precise measurement, compared with the conventional methods.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.258-268
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• 2021

Point cloud content is immersive content that represents real-world objects with three-dimensional (3D) points. In the process of acquiring point cloud data or encoding and decoding point cloud data, the resolution of point cloud content could be degraded. In this paper, we propose a method of progressively enhancing the resolution of sequential point cloud contents through inter-frame registration. To register a point cloud, the iterative closest point (ICP) algorithm is commonly used. Existing ICP algorithms can transform rigid bodies, but there is a disadvantage that transformation is not possible for non-rigid bodies having motion vectors in different directions locally, such as point cloud content. We overcome the limitations of the existing ICP-based method by registering regions with motion vectors in different directions locally between the point cloud content of the current frame and the previous frame. In this manner, the resolution of the point cloud content with geometric movement is enhanced through the process of registering points between frames. We provide four different point cloud content that has been enhanced with our method in the experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.15-19
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• 2001

A dedicated reverse engineering(RE) system for rapid manufacturing of human head in a 3D bust has been developed. The first step in the process is to capture the surface details of a human head and shoulder by three scanners based upon the digital moire fringe technique. Then the multiple scans captured from different angles are aligned and merged into a single polygonal mesh, and the aligned data set is refined by smoothing, subdividing or hole filling process. Finally, the refined data set is sent to a 4-axis computer numerically control(NC) machine to manufacture a replica. In this paper, we mainly describe on the algorithms and software for aligning multiple data sets. The method is based on the recently popular Iterative Closest Point(ICP) algorithm that aligns different polygonal meshes into one common coordinate system. The ICP algorithm finds the nearest positions on one scan to a collection of points on the other scan by minimizing the collective distance between different scans. We also integrate some heuristics into the ICP to enhance the aligning process. A typical example is presented to validate the system and further research work is also discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.597-602
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• 2016

In image guided surgery, a patient registration process is a critical process for the successful operation, which is required to use pre-operative images such as CT and MRI during operation. Though several patient registration methods have been studied, we concentrate on one method that utilizes 3D surface measurement data in this paper. First, a hand-held 3D surface measurement device measures the surface of the patient, and secondly this data is matched with CT or MRI data using optimization algorithms. However, generally used ICP algorithm is very slow without a proper initial location and also suffers from local minimum problem. Usually, this problem is solved by manually providing the proper initial location before performing ICP. But, it has a disadvantage that an experience user has to perform the method and also takes a long time. In this paper, we propose a method that can accurately find the proper initial location automatically. The proposed method finds the proper initial location for ICP by converting 3D data to 2D curvature images and performing image matching. Curvature features are robust to the rotation, translation, and even some deformation. Also, the proposed method is faster than traditional methods because it performs 2D image matching instead of 3D point cloud matching.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.248-253
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• 2011

This paper proposes the robust matching algorithm for optical images obtained by WSI(White-light Scanning Interferometer) machine. The matching algorithms are divided by two part according to the matching points: algorithm whether the matching points between two images exist or not. Also, after matching the images, we propose the algorithm to smooth the matched image. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.