• 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.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.567-576
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• 2005

This paper proposes an image-based modeling method which recovers 3D models using projected line segments in multiple images. Using the method, a user obtains accurate 3D model data via several steps of simple manual works. The embedded nonlinear minimization technique in the model parameter estimation stage is based on the distances between the user provided image line segments and the projected line segments of primitives. We define an error using a finite line segment and thus increase accuracy in the model parameter estimation. The error is defined as the sum of differences between the observed image line segments provided by the user and the predicted image line segments which are computed using the current model parameters and camera parameters. The method is robust in a sense that it recovers 3D structures even from partially occluded objects and it does not be seriously affected by small measurement errors in the reconstruction process. This paper also describesexperimental results from real images and difficulties and tricks that are found while implementing the image-based modeler.

• Current Optics and Photonics
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• v.4 no.6
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• pp.545-550
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• 2020

We propose a hole-filling method to solve discontinuous depth representation and to reduce the visible seams and cracks that cause the limitation of the viewing angle of the three-dimensional (3D) image in the multilayer type 3D display system. The occlusion and the disocclusion regions between layers, such as the visible seams and cracks, are a major bottleneck of the multilayer type 3D display system to represent a volumetric 3D image by stacking multiple images. As a result, in the reconstructed 3D image, the visible seams and cracks appear as brighter overlapping and undesirable cut-off. In order to resolve the problems above, we applied the depth-fused effect to the sub-depth map generating algorithm and improve the viewing characteristics of the multilayer type 3D display. The experimental demonstrations are also provided to verify the proposed scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.127-135
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• 2006

The image-based 3D modeling is the technique of generating a 3D graphic model from images acquired using cameras. It is being researched as an alternative technique for the expensive 3D scanner. In this paper, I propose the image-based 3D modeling system using calibrated camera. The proposed algorithm for rendering 3D model is consisted of three steps, camera calibration, 3D shape reconstruction and 3D surface generation step. In the camera calibration step, I estimate the camera matrix for the image aquisition camera. In the 3D shape reconstruction step, I calculate 3D volume data from silhouette using pyramidal volume intersection. In the 3D surface generation step, the reconstructed volume data is converted to 3D mesh surface. As shown the result, I generated relatively accurate 3D model.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.370-374
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• 2009

In this paper, we presents a new cone beam computerized tomography (CB CT) system for the reconstruction of 3 dimensional dynamic images. The system using cone beam has less the exposure of radioactivity than fan beam, relatively. In the system, the reconstruction 3-D image is reconstructed with the radiation angle of X-ray in the image processing unit and transmitted to the monitor. And in the image processing unit, the Three Pass Shear Matrices, a kind of Rotation-based method, is applied to reconstruct 3D image because it has less transcendental functions than the one-pass shear matrix to decrease a time of calculations for the reconstruction 3-D image in the processor. The new system is able to get 3~5 3-D images a second, reconstruct the 3-D dynamic images in real time.

• Progress in Medical Physics
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• v.10 no.1
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• pp.33-40
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• 1999

Purpose: To simulate and measure the signal intensity of various tissues near bone interface in 2D and 3D neurological MR images. Materials and Methods: In neurological proton density (PD) weighted images, every component in the head including cerebrospinal fluid (CSF), muscle and scalp, with the exception of bone, are visualised. It is possible to acquire images in 2D or 3D. A 2D fast spin-echo (FSE) sequence is chosen for the 2D acquisition and a 3D gradient-echo (GE) sequence is chosen for the 3D acquisition. To find out the signal intensities of CSF, muscle and fat (or scalp) for the 2D spin-echo(SE) and 3D gradient-echo (GE) imaging sequences, the theoretical signal intensities for 2D SE and 3D GE were calculated. For the 2D fast spin-echo (FSE) sequence, to produce the PD weighted image, long TR (4000 ms) and short TE$_{eff}$ (22 ms) were employed. For the 3D GE sequence, low flip angle (8$^{\circ}$) with short TR (35 ms) and short TE (3 ms) was used to produce the PD weighted contrast. Results: The 2D FSE sequence has CSF, muscle and scalp with superior image contrast and SNR of 39 - 57 while the 3D GE sequence has CSF, muscle and scalp with broadly similar image contrast and SNR of 26 - 33. SNR in the FSE image were better than those in the GE image and the skull edges appeared very clearly in the FSE image due to the edge enhancement effect in the FSE sequence. Furthermore, the contrast between CSF, muscle and scalp in the 2D FSE image was significantly better than in the 3D GE image, due to the strong signal intensities (or SNR) from CSF, muscle and scalp and enhanced edges of CSF. Conclusion: The signal intensity of various tissues near bone interface in neurological MR images has been simulated and measured. Both the simulation and imaging of the 2D SE and 3D GE sequences have CSF, fat and muscle with broadly similar image intensity and SNR's and have succeeded in getting all tissues about the same signal. However, in the 2D FSE sequence, image contrast between CSF, muscle and scalp was good and SNR was relatively high, imaging time was relatively short.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1363-1366
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• 2009

A new recognition method is used to find the three-dimensional target object on integral imaging. For finding the location of a target image, amount of reconstructed reference image is needed. This method is giving accurate information of target image by correlated among reconstructed target images and reference images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9C
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• pp.555-563
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• 2011

In this paper, we propose an object based 2D image to 3D conversion algorithm by using motion estimation, color labeling and non-local mean filtering methods. In the proposed algorithm, we first extract the motion vector of each object by estimating the motion between frames and then segment a given image frame with color labeling method. Then, combining the results of motion estimation and color labeling, we extract object regions and assign an exact depth value to each object to generate the right image. While generating the right image, occlusion regions occur but they are effectively recovered by using non-local mean filter. Through the experimental results, it is shown that the proposed algorithm performs much better than conventional conversion scheme by removing the eye fatigue effectively.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2007.02a
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• pp.53-57
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• 2007

This paper presents the practice of multitexturing in the Internet for enhancing the image quality of 3D contents, where the attributes of objects such as textures are dynamically changed. We explain the empirical results of realizing the X3D nodes related with multitexturing in the recent X3D viewers, and discuss the directions for upgrading X3D viewers that satisfy the user requirements and the advanced graphics accelerators.