• Journal of Biomedical Engineering Research
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• v.19 no.2
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• pp.189-198
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• 1998

3D medical image reconstruction techniques are useful to figure out complex 3D structures from the set of 2D sections. In the paper, 3D medical image reconstruction system is constructed under PC environment and programmed based on modular programming by using Visual C++ 4.2. The whole procedures are composed of data preparation, gradient estimation, classification, shading, transformation and ray-casting & compositing. Three speed optimization techniques are used for accelerating 3D medical image reconstruction technique. One is to reduce the rays when cast rays to reconstruct 3D medical image, another is to reduce the voxels to be calculated and the other is to apply early ray termination. To implement 3D medical image reconstruction system based on PC, speed optimization techniques are experimented and applied.

• The Journal of the Korea Contents Association
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• v.9 no.5
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• pp.13-23
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• 2009

One of the main purpose of multiple-view image processing technology is support realistic 3D image to device user by using multiple viewpoint display devices and compressed data restoration devices. This paper proposes a multiple view image synthesis scheme based on RAM disk which makes possible to browse 3D images generated by applying effective composing method to real time input stereo images. The proposed scheme first converts input images to binary image. We applies edge detection algorithm such as Sobel algorithm and Prewiit algorithm to find edges used to evaluate disparities from images of 4 multi-cameras. In addition, we make use of time interval between hardware trigger and software trigger to solve the synchronization problem which has stated ambiguously in related studies. We use a unique identifier on each snapshot of images for distributed environment. With respect of performance results, the proposed scheme takes 0.67 sec in each binary array. to transfer entire images which contains left and right side with disparity information for high quality 3D image browsing. We conclude that the proposed scheme is suitable for real time 3D applications.

• Journal of Korea Multimedia Society
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• v.22 no.1
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• pp.55-61
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• 2019

Almost all 3D displays have a brightness reduction in the 3D mode comparing to the 2D mode. When the brightness is reduced, one of the color attributes, the colorfulness, is decreased. In this case, the viewer feels that the image quality is deteriorated. In this paper, we proposed a method to compensate for the degradation of colorfulness due to brightness reduction in 3D mode for high quality 3D image viewing using the CIECAM02 model and the color correction matrix. As a result of applying the proposed method, we can confirm that the colorfulness is improved in 3D mode.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3121-3142
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• 2017

We present a method for 3D shape reconstruction of inextensible deformable surfaces from a single image. The key of our approach is to represent the surface as a 3D triangulated mesh and formulate the reconstruction problem as a sequence of Linear Programming (LP) problems. The LP problem consists of data constraints which are 3D-to-2D keypoint correspondences and shape constraints which are designed to retain original lengths of mesh edges. We use a closed-form method to generate an initial structure, then refine this structure by solving the LP problem iteratively. Compared with previous methods, ours neither involves smoothness constraints nor temporal consistency, which enables us to recover shapes of surfaces with various deformations from a single image. The robustness and accuracy of our approach are evaluated quantitatively on synthetic data and qualitatively on real data.

• Journal of Biomedical Engineering Research
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• v.26 no.4
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• pp.185-191
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• 2005

In this paper, we proposed a downscaled 3D object technique using medical images for telediagnostic use. The proposed system consisted of downscaling/thresholding processes for building a downscaled 3D object and a process for obtaining 2D images at specific angles for diagnosis support. We used 80 slices of Digital Imaging and Communication in Medicine(DICOM) CT images as sample images and the platform-independent Java language for the experiment. We confirmed that the total image set size and transmission time of the original DICOM image set using a down-scaled 3D object decreased approximately $99\%\;and\;98.41\%,$ respectively. With additional studies, the proposed technique obtained from these results will become useful in supporting diagnosis for home and hospital care.

• Proceedings of the Korea Contents Association Conference
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• 2015.05a
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• pp.347-348
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• 2015

최근 들어 3D데이터의 필요성이 대두되면서 여러 콘텐츠가 개발되고 있다. 2D image를 3D로 변환하기 위해 Canny 에지 검출알고리즘을 이용하였다. 이와 같은 3D 모델로 제작한 데이터는 3D 애니메이션이 가능하므로 과학관 등의 전시실에 활용 할 수 있다.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.281-291
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• 2019

Depth from defocus estimates the 3D depth by using a phenomenon in which the object in the focal plane of the camera forms a clear image but the object away from the focal plane produces a blurred image. In this paper, algorithms are studied to estimate 3D depth by analyzing the degree of blur of the image taken with a single camera. The optimized object range was obtained by 3D depth estimation derived from depth from defocus using one image of a single camera or two images of different focus of a single camera. For depth estimation using one image, the best performance was achieved using a focal length of 250 mm for both smartphone and DSLR cameras. The depth estimation using two images showed the best 3D depth estimation range when the focal length was set to 150 mm and 250 mm for smartphone camera images and 200 mm and 300 mm for DSLR camera images.

• Journal of KIISE:Databases
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• v.32 no.4
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• pp.383-393
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• 2005

Retrieval of images from image databases by spatial relationship can be effectively performed through visual interface systems. In these systems, the representation of image with 2D strings, which are derived from symbolic projections, provides an efficient and natural way to construct image index and is also an ideal representation for the visual query. With this approach, retrieval is reduced to matching two symbolic strings. However, using 2D-string representations, spatial relationships between the objects in the image might not be exactly specified. Ambiguities arise for the retrieval of images of 3D scenes. In order to remove ambiguous description of object spatial relationships, in this paper, images are referred by considering spatial relationships using the spatial location algebra for the 3D image scene. Also, we remove the repetitive spatial relationships using the several reduction rules. A reduction mechanism using these rules can be used in query processing systems that retrieve images by content. This could give better precision and flexibility in image retrieval.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.426-429
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• 2004

To reconstruct the 3-D information of a irregular object, this paper proposes a new method applying the composition focus measure to time-series image. A focus measure function is carefully selected because a focus measure is apt to be affected by the working environment and the characteristics of an object. The proposed focus measure function combines the variance measure which is robust to noise and the Laplacian measure which, regardless of an object shape, has a good performance in calculating the focus measure. And the time-series image, which considers the object shape, is proposed in order to efficiently applying the interesting window. This method, first, divides the image frame by the window. Second, the composition focus measure function be applied to the windows, and the time-series image is constructed. Finally, the 3-D information of an object is reconstructed from the time-series images considering the object shape. The experimental results have shown that the proposed method is suitable algorithm to 3-D reconstruction of an irregular object.

• Journal of Digital Convergence
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• v.10 no.4
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• pp.191-197
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• 2012

In this paper we present creating 3D image from 2D image by extract initial depth values calculated from focal values. The initial depth values are created by using the extracted focal information, which is calculated by the comparison of original image and Gaussian filtered image. This initial depth information is allocated to the object segments obtained from normalized cut technique. Then the depth of the objects are corrected to the average of depth values in the objects so that the single object can have the same depth. The generated depth is used to convert to 3D image using DIBR(Depth Image Based Rendering) and the generated 3D image is compared to the images generated by other techniques.