• Journal of the Korean Society of Radiology
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• v.81 no.1
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• pp.81-100
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• 2020

Magnetic resonance neurography (MRN) has been increasingly used in recent years for the assessment of peripheral neuropathies. Fat suppression T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) have typically been used to provide high contrast MRN. Isotropic 3-dimensional (3D) sequences with fast spin echo, post-processing imaging techniques, and fast imaging methods, among others, allow good visualization of peripheral nerves that have a small diameter, complex anatomy, and oblique course within a reasonable scan time. However, there are still several issues when performing high contrast and high resolution MRN including standard sequence; fat saturation techniques; balance between resolution, field of view, and slice thickness; post-processing techniques; 2D vs. 3D image acquisition; different T2 contrasts between proximal and distal nerves; high T2 signal intensity of adjacent veins or joint fluid; geometric distortion; and appropriate p-values on DWI. The proper understanding of these issues will help novice radiologists evaluate peripheral neuropathies using MRN.

• The KIPS Transactions:PartB
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• v.16B no.6
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• pp.451-462
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• 2009

The spread of satellite image increases various services using it. Especially, 3D visualization services of the whole earth such as $Google\;Earth^{TM}$ and $Virtual\;Earth^{TM}$ or 3D GIS services for several cities provide realistic geometry information of buildings and terrain of wide areas. These service can be used in the various fields such as urban planning, improvement of roads, entertainment, military simulation and emergency response. The research about extracting the building and terrain information effectively from the high-resolution satellite image is required. In this paper, presents a system for effective extraction of the building model from a single high-resolution satellite image, after examine requirements for building model extraction. The proposed system utilizes geometric features of satellite image and the geometric relationship among the building, the shadow of the building, the positions of the sun and the satellite to minimize user interaction. Finally, after extracting the 3D building, the fact that effective extraction of the model from single high-resolution satellite will be show.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3782-3796
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• 2020

A three-dimensional (3D) reconstruction is an important research area in computer vision. The ability to detect and match features across multiple views of a scene is a critical initial step. The tracking matrix W obtained from a 3D reconstruction can be applied to structure from motion (SFM) algorithms for 3D modeling. We often fail to generate an acceptable number of features when processing face or medical images because such images typically contain large homogeneous regions with minimal variation in intensity. In this study, we seek to locate sufficient matching points not only in general images but also in face and medical images, where it is difficult to determine the feature points. The algorithm is implemented on an adaptive threshold value, a scale invariant feature transform (SIFT), affine SIFT, speeded up robust features (SURF), and affine SURF. By applying the algorithm to face and general images and studying the geometric errors, we can achieve quasi-dense matching points that satisfy well-functioning geometric constraints. We also demonstrate a 3D reconstruction with a respectable performance by applying a column space fitting algorithm, which is an SFM algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10c
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• pp.52-54
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• 2001

3차원 그래픽 가속기는 지오메트리 처리(geometry processing)와 레스터라이져(rasterizer)로 구성된다. 본 논문에서는 지오메트리 처리들 고속으로 수행할 수 있는 벡터 형태의 처리 구조(VGE)를 제안하였다. 특허 기존의 부동소수점을 계산할 수 있는 구조에 4개의 FADD, FMUL, 128개의 벡터 레지스터를 추가하여 지오메트리 연산을 가속했으며 VGE와 비슷한 H/W 비용을 갖는 Hitachi의 SH4와 비교했을 때 평균 4.7배의 성능향상을 보였다. 또한 성능 평가를 위해 범용프로세서 시뮬레이터인 Simplescalar를 수정하여 시뮬레이터를 제작했으며 Viewperf Benchmark를 입력으로 사용하였다.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.2
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• pp.69-79
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• 1994

The conventional machine vision system which has uniform rectangular grid requires tremendous amount of computation for processing and analysing an image especially in 2-D image transfermations such as scaling, rotation and 3-D reconvery problem typical in robot application environment. In this study, the imaging system with nonuiformly distributed image sensors simulating human visual system, referred to as Ploar Exponential Grid(PEG), is compared with the existing conventional uniform rectangular grid system in terms of image resolution and computational complexity. By mimicking the geometric structure of the PEG sensor cell, we obtained PEG-like images using computer simulation. With the images obtained from the simulation, image resolution of the two systems are compared and some basic image processing tasks such as image scaling and rotation are implemented based on the PEG sensor system to examine its performance. Furthermore Fourier transform of PEG image is described and implemented in image analysis point of view. Also, the range and heading-angle measurement errors usually encountered in 3-D coordinates recovery with stereo camera system are claculated based on the PEG sensor system and compared with those obtained from the uniform rectangular grid system. In fact, the PEC imaging system not only reduces the computational requirements but also has scale and rotational invariance property in Fourier spectrum. Hence the PEG system has more suitable image coordinate system for image scaling, rotation, and image recognition problem. The range and heading-angle measurement errors with PEG system are less than those of uniform rectangular rectangular grid system in practical measurement range.

• Journal of Sensor Science and Technology
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• v.33 no.3
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• pp.179-184
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• 2024

In the car industry, welding is a fundamental linking technique used for joining components, such as steel, molds, and automobile parts. However, accurate inspection is required to test the reliability of the welding components. In this study, we investigate the detection of weld beads using 2D image processing in an automatic recognition system. The sample image is obtained using a 2D vision camera embedded in a lighting system, from where a portion of the bead is successfully extracted after image processing. In this process, the soot removal algorithm plays an important role in accurate weld bead detection, and adopts adaptive local gamma correction and gray color coordinates. Using this automatic recognition system, geometric parameters of the weld bead, such as its length, width, angle, and defect size can also be defined. Finally, on comparing the obtained data with the industrial standards, we can determine whether the weld bead is at an acceptable level or not.

• The KIPS Transactions:PartA
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• v.16A no.2
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• pp.61-68
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• 2009

We present a fast 3D shape deformation method that achieves smoothly deformed result by approximating a rigid transformation based on moving least squares (MLS). Our modified MLS formulation reduces the computation cost for computing the optimal transformation of each point and still keeps the rigidity of the deformed results. Even complex geometric shapes are easily, intuitively, and interactively deformed by manipulating point and ellipsoidal handles.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.403-410
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• 2004

Recently, studies of image analysis, as the preprocessing stage for medical image analysis or image retrieval, are actively carried out. This paper intends to propose a way of utilizing color components for image retrieval. For image retrieval, it is based on color components, and for analysis of color, CLCM (Color Level Co-occurrence Matrix) and statistical techniques are used. CLCM proposed in this paper is to project color components on 3D space through geometric rotate transform and then, to interpret distribution that is made from the spatial relationship. CLCM is 2D histogram that is made in color model, which is created through geometric rotate transform of a color model. In order to analyze it, a statistical technique is used. Like CLCM, GLCM (Gray Level Co-occurrence Matrix)[1] and Invariant Moment [2,3] use 2D distribution chart, which use basic statistical techniques in order to interpret 2D data. However, even though GLCM and Invariant Moment are optimized in each domain, it is impossible to perfectly interpret irregular data available on the spatial coordinates. That is, GLCM and Invariant Moment use only the basic statistical techniques so reliability of the extracted features is low. In order to interpret the spatial relationship and weight of data, this study has used Principal Component Analysis [4,5] that is used in multivariate statistics. In order to increase accuracy of data, it has proposed a way to project color components on 3D space, to rotate it and then, to extract features of data from all angles.

• Journal of Biosystems Engineering
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• v.33 no.3
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• pp.196-203
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• 2008

Hybrid robust image processing algorithm to extract visual features of melon during the cultivation was developed based on a wireless tele-operative interface. Features of a melon such as size and shape including position were crucial to successful task automation and future development of cultivation data base. An algorithm was developed based on the concept of hybrid decision-making which shares a task between the computer and the operator utilizing man-computer interactive interface. A hybrid decision-making system was composed of three modules such as wireless image transmission, task specification and identification, and man-computer interface modules. Computing burden and the instability of the image processing results caused by the variation of illumination and the complexity of the environment caused by the irregular stem and shapes of leaves and shades were overcome using the proposed algorithm. With utilizing operator's teaching via LCD touch screen of the display monitor, the complexity and instability of the melon identification process has been avoided. Hough transform was modified for the image obtained from the locally specified window to extract the geometric shape and position of the melon. It took less than 200 milliseconds processing time.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.153-158
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• 1998

Since the mid-1990′s, researches on 3D GIS have been regarded as one of main issues both in the academic sites and commercial vendors; recently, some prototyped systems or the first versioned software systems of commercial basis are being reported and released. Unlike conventional 2D GIS, which consists in intelligent structured GIS or desktop GIS, every 3D GIS has its own distinguished features according to data structure-supporting capability, GIS-styled functionality, external database accessibility, interfacing extents with 2D GIS, 3D visualization/texture mapping ability, and so forth. In this study, technical aspects related to system development, SERI-Web3D GIS ver. 1.2, are explained. Main features in this revised 3D GIS can be summarized: 2-tier system model(client-server), VGFF(Virtual GIS File Format), internal GIS import, Feature manager(zoning, layering, visualization evironment), Scene manager(manage 3D geographic world), Scene editor, Spatial analyzer(Intersect, Buffering, Network analysis), VRML exporter. While, most other 3D GISes or cartographic mapping systems may be categorized into 3D visualization systems handling terrain height-field processing, 2D GIS extension modules, or 3D geometric feature generation system using orthophoto image: actually, these are eventually considered as several parts of "real 3D GIS". As well as these things, other components, especially web-based 3D GIS, are being implemented in this study: Surface/feature integration, Java/VRML linkage, Mesh/Grid problem, LOD(Level of Detail)/Tiling, Public access security problem, 3-tier architecture extension, Surface handling strategy for VRML.