• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.402-407
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• 2004

Since the world wide web, simple and convenient tool, has proposed, the Internet became the most simple network resource which provide many informations of the world. Furthermore, various methodologies are developed to support the dynamic service such as 3D View web service. We will propose the volume rendering view program that interactively visualize the 3D data on the web. The 3D Data is obtained by stacking the 2D images along the z-direction. We also employ the COM based OCX control which is a kind of Active component. This web program will contribute the diagnosis of the diseases through the 3D visualization and image analysis functions at remote places.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1885-1888
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• 2004

In order to render 3D model of the bone, the stack of cross-sectional images must be reconstructed from a series of X-ray radiographs, served as the projections. In the case where the distance between x-ray source and detector is not infinite, image reconstruction from projection based on parallel-beam geometry provides an error in the cross-sectional image. In such case, image reconstruction from projection based on conebeam geometry must be exercised instead. This paper is devoted to the determination of detector center for SART conebeam Technique which is critically effect the performance of the resulting 3D modeling.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.3_4
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• pp.138-148
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• 2003

Orthogonal Cross Cylinder mapping and segmentation based modeling methods have been implemented for constructing the image-based navigation system in this paper. The Orthogonal Cross Cylinder (OCC) is the object expressed by the intersection area that occurs when a cylinder is orthogonal with another. OCC mapping method eliminates the singularity effect caused in the environment maps and shows an almost even amount of area for the environment occupied by a single texel. A full-view image from a fixed point-of-view can be obtained with OCC mapping although it becomes difficult to express another image when the point-of-view has been changed. The OCC map is segmented according to the objects that form the environment and the depth value is set by the characteristics of the classified objects for the segmentation based modeling. This method can easily be implemented on an environment map and makes the environment modeling easier through extracting the depth value by the image segmentation. An environment navigation system with a full-view can be developed with these methods.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.255-262
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• 2002

The Virtual Reality (VR) is an appealing subject which can be applied to various areas because of its merit - removal of time limits and space. Recently, as the technology of xDSL spreads widely, a concern of VR is on the on-line service of 3D model data in real time. But, the immensity of 3D model is an obstacle to achieve these endeavors. To solve these problems, the image based VR technique is applied. The proposed method in this paper is one of solutions on the immensity problem of 3D model data in the on-line services. This paper exploits the mixed technique of image based VR and surface rendering based on volume rendering. By using the proposed method, we can solve the immensity problem. Consequently, tole service user can explore virtual 2D volume model with almost equal to reality of 3D volume model. Furthermore, this paper explains a method to implement this service on general web environments. Of course, to fulfill these procedures, additional skills which reduce consuming time in data mining are also mentioned. The contribution of this paper is to provide a practical method for handling of large volume data web service in real-time. illustrative examples are presented to show the effectiveness of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.48-60
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• 2011

Nowadays, the 3D community is actively researching on 3D imaging and free-viewpoint video (FVV). The free-viewpoint rendering in multi-view video, virtually move through the scenes in order to create different viewpoints, has become a popular topic in 3D research that can lead to various applications. However, there are restrictions of cost-effectiveness and occupying large bandwidth in video transmission. An alternative to solve this problem is to generate virtual views using a single texture image and a corresponding depth image. A critical issue on generating virtual views is that the regions occluded by the foreground (FG) objects in the original views may become visible in the synthesized views. Filling this disocclusions (holes) in a visually plausible manner determines the quality of synthesis results. In this paper, a new approach for handling disocclusions using depth based inpainting algorithm in synthesized views is presented. Patch based non-parametric texture synthesis which shows excellent performance has two critical elements: determining where to fill first and determining what patch to be copied. In this work, a noise-robust filling priority using the structure tensor of Hessian matrix is proposed. Moreover, a patch matching algorithm excluding foreground region using depth map and considering epipolar line is proposed. Superiority of the proposed method over the existing methods is proved by comparing the experimental results.

• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.846-855
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• 2007

Significant feature extraction in cancer cell image analysis is an important process for grading cell carcinoma. In this study, we propose a method for 3D quantitative analysis of cell nuclei based upon digital image cytometry. First, we acquired volumetric renal cell carcinoma data for each grade using confocal laser scanning microscopy and segmented cell nuclei employing color features based upon a supervised teaming scheme. For 3D visualization, we used a contour-based method for surface rendering and a 3D texture mapping method for volume rendering. We then defined and extracted the 3D morphological features of cell nuclei. To evaluate what quantitative features of 3D analysis could contribute to diagnostic information, we analyzed the statistical significance of the extracted 3D features in each grade using an analysis of variance (ANOVA). Finally, we compared the 2D with the 3D features of cell nuclei and analyzed the correlations between them. We found statistically significant correlations between nuclear grade and 3D morphological features. The proposed method has potential for use as fundamental research in developing a new nuclear grading system for accurate diagnosis and prediction of prognosis.

• Cartoon and Animation Studies
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• s.36
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• pp.493-510
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• 2014

From game consoles to TV and Hollywood films, 3D rendering technology is involved in various fields. Up until the late 90s, the computer image rendering method was rasterization that mainly used Phong Shading, and up until recently it was the go-to method for movies and film animation. In the 21st century, the quality provided by Ray Tracing and the development of Global Illumination was much more realistic and thus became popularized. However, despite its growing use in architectural rendering to the markets, Global Illumination in film animation and movies was limited due to its long render time. So, in this thesis, if one were to take the concept from each rendering method and consider it from a mathematical perspective, one could adapt the Ambient Occlusion's equation to the illumination loop equation used in rasterization. This algorithm modification has the capability to reflect the lighting of a diverse array of colors, like in Global Illumination, with a fast render time, as in rasterization, and the example RenderMan Shader is based upon this new algorithm. In conclusion, with Global Illumination's naturalistic lighting and rasterization's rendering speed, the combination of the best points of each is a new method with a short rendering time while producing good quality. I hope animations and films can benefit from this algorithm by the reduction of budget with an overall better quality output in VFX production.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1126-1134
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• 2017

A variety of medical service applications in the field of the Internet of Things (IoT) are being studied. Segmentation is important to identify meaningful regions in images and is also required in 3D images. Previous methods have been based on gray value and shape. The Visible Korean dataset consists of serially sectioned high-resolution color images. Unlike computed tomography or magnetic resonance images, automatic segmentation of color images is difficult because detecting an object's boundaries in colored images is very difficult compared to grayscale images. Therefore, skilled anatomists usually segment color images manually or semi-automatically. We present an out-of-core 3D segmentation method for large-scale image datasets. Our method can segment significant regions in the coronal and sagittal planes, as well as the axial plane, to produce a 3D image. Our system verifies the result interactively with a multi-planar reconstruction view and a 3D view. Our system can be used to train unskilled anatomists and medical students. It is also possible for a skilled anatomist to segment an image remotely since it is difficult to transfer such large amounts of data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.11
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• pp.919-927
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• 2013

In this paper, we present a perception-based tone mapping technique using histogram modification for displaying high dynamic range image. HDR (high dynamic range) tone mapping algorithms are used to display HDR image on LDR (low dynamic rnage) devices. Although perception-based tone mapping methods provides better performance, it dose not always produce good results for a wide variety of images. The proposed method reduces dynamic range by using the perception-based tone mapping function and histogram modification. A derivative of perception-based tone mapping function is used as constraint function of histogram and additional compensation process is performed. This method not only improves contrast by adopting different constraints on each pixel value, but also preserves more visual details. In order to prevent over enhancement, histogram modification technique is applied. Furthermore, it can control the rate of image contrast using control parameters. Subjective and objective evaluations show that proposed algorithm is better than existing algorithms.

• Journal of Korea Multimedia Society
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• v.23 no.3
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• pp.468-475
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• 2020

In this paper, we proposed a three-dimensional visualization system for medical images in augmented reality based on deep learning. In the proposed system, the artificial neural network model performed fully automatic segmentation of the region of lung and pulmonary nodule from chest CT images. After applying the three-dimensional volume rendering method to the segmented images, it was visualized in augmented reality devices. As a result of the experiment, when nodules were present in the region of lung, it could be easily distinguished with the naked eye. Also, the location and shape of the lesions were intuitively confirmed. The evaluation was accomplished by comparing automated segmentation results of the test dataset to the manual segmented image. Through the evaluation of the segmentation model, we obtained the region of lung DSC (Dice Similarity Coefficient) of 98.77%, precision of 98.45%, recall of 99.10%. And the region of pulmonary nodule DSC of 91.88%, precision of 93.05%, recall of 90.94%. If this proposed system will be applied in medical fields such as medical practice and medical education, it is expected that it can contribute to custom organ modeling, lesion analysis, and surgical education and training of patients.