• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.977-991
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• 2000

In this paper, a medical image processing system was designed and implemented for morphometric and functional analysis of a human brain. The system is composed of image registration, ROI(region of interest) analysis, functional analysis, image visualization, 3D medical image database management system(DBMS), and database. The software processes an anatomical and functional image as input data, and provides visual and quantitative results. Input data and intermediate or final output data are stored to the database as several data types by the DBMS for other further image processing. In the experiment, the ROI analysis, for a normal, a tumor, a Parkinson's decease, and a depression case, showed that the system is useful for morphometric and functional analysis of a human brain.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.248-251
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• 2007

In this paper, we are propose a method to estimate the 2-D mesh from structured light image for reconstruction of 3-D face image. To acquire the structured light image, we are project structured light on the face using the projector. we are extract the projected cross points from the acquire image. The 2-D mesh image is extracted from the position and angle of cross points. In the extraction processing, the error was fixed to extract the correct 2-D mesh.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.107-114
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• 2022

In order to classify 3D film images as right or wrong, it is necessary to detect the pattern in a 3D film image. However, if the contrast of the pixels in the 3D film image is low, it is not easy to classify as the right and wrong 3D film images because the pattern in the image might not be clear. In this paper, we propose a method of classifying 3D film images as right or wrong by comparing the width at a specific frequency of each histogram after obtaining the histogram. Since, it is classified using the width of the histogram, the analysis process is not complicated. From the experiment, the histograms of right and wrong 3D film images were distinctly different, and the proposed algorithm reflects these features, and showed that all 3D film images were accurately classified at a specific frequency of the histogram. The performance of the proposed algorithm was verified to be the best through the comparison test with the other methods such as image subtraction, otsu thresholding, canny edge detection, morphological geodesic active contour, and support vector machines, and it was shown that excellent classification accuracy could be obtained without detecting the patterns in 3D film images.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.359-366
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• 2003

We propose a real-time stereoscopic image conversion method that can generate stereoscopic image with different perspective depth using motion parallax from 2-D image and offer realistic 3-D effect regardless of the direction and velocity of the moving object in the 2-D image. The stereoscopic image is generated by computing the motion parallax between adjacent two 2-D images using the proposed method for motion detection, region segmentation and depth map generation. The proposed method is suitable for real-time stereoscopic conversion processing on various image formats. It has been verified the proposed method by comparing between the stereoscopic image of the proposed method and that of MTD.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.351-356
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• 2006

Based on current practical needs for geo-spatial information on mobile platform, the main theme of this study is a design and implementation of dynamic 3D terrain rendering system using spaceborne imagery, as a kind of texture image for photo-realistic 3D scene generation on mobile environment. Image processing and 3D graphic techniques and algorithms, such as TIN-based vertex generation with regular spacing elevation data for generating 3D terrain surface, image tiling and image-vertex texturing in order to resolve limited resource of mobile devices, were applied and implemented by using graphic pipeline of OpenGL|ES (Embedded System) API. Through this implementation and its tested results with actual data sets of DEM and satellite imagery, we demonstrated the realizable possibility and adaptation of complex typed and large sized 3D geo-spatial information in mobile devices. This prototype system can be used to mobile 3D applications with DEM and satellite imagery in near future.

• 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.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.252-260
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• 2016

The performance of human detection system is affected by camera location and view angle. In 2D image acquired from such camera settings, humans are displayed in different sizes. Detecting all the humans with diverse sizes poses a difficulty in realizing a real-time system. However, if the size of a human in an image can be predicted, the processing time of human detection would be greatly reduced. In this paper, we propose a method that estimates human size by constructing an indoor scene in 3D space. Since the human has constant size everywhere in 3D space, it is possible to estimate accurate human size in 2D image by projecting 3D human into the image space. Experimental results validate that a human size can be predicted from the proposed method and that machine-learning based detection methods can yield the reduction of the processing time.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.1309-1312
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• 2000

컴포넌트를 기반으로 하는 소프트웨어 개발 방법론은 시스템의 규모가 크고 구성이 복잡한 지리정보 시스템에 효율적으로 적응될 수 있다. 이것은 특히 개방형 GIS를 위한 설계와 구현 방법에도 이용되고 있다. 본 논문에서는 복합 피쳐를 지원하는 3차원 지리정보시스템의 컴포넌트 기반 설계 사례에 대해 설명한다. 본 논문에서 제안한 시스템은 OpenGIS 규격과의 호환성을 고려하고 복합 피쳐 및 복합 지리요소를 지원하며 객체 지향 분석 설계 방법론을 이용하여 설계되었다. 본 시스템은 3차원 지리요소의 모델링, 가시화, 공간분석 기능과 4차원 공간 데이터에 대한 질의 기능을 포함하고 있다. 향 후 복잡한 도심 건물 지역을 대상으로 층별 시공간 관리 분석 시스템 등으로 응용될 전망이다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.3
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• pp.111-121
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• 2016

In this study, measurements were conducted by image processing to do an in-depth evaluation of strain of rebar in a uniaxial tension test. The distribution of strain and the necking region were evaluated. The image processing is used to analyze the color information of a colored image, so that the parts consistent with desired targets can be distinguished from the other parts. After this process, the image was converted to a binary one. Centroids of each target region are obtained in the binary images. After repeating such process on the images from starting point to the finishing point of the test, elongation between targets is calculated based on the centroid of each target. The tensile test were conducted on grade 60 #7(D22) and #9(D29) rebars fabricated in accordance with ASTM A615 standards. Strain results from image processing were compared to the results from a conventional strain gauge, in order to see the validity of the image processing. With the image processing, the measuring was possible in not only the initial elastic region but also the necking region of more than 0.5(50%) strain. The image processing can remove the measuring limits as long as the targets can be video recorded. It also can measure strain at various spots because the targets can easily be attached and detached. Thus it is concluded that the image processing helps overcome limits in strain measuring and will be used in various ways.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.1
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• pp.30-37
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• 2021

Accurate 3D object tracking with camera images is a key enabling technology for augmented reality applications. Motivated by the impressive success of convolutional neural networks (CNNs) in computer vision tasks such as image classification, object detection, image segmentation, recent studies for 3D object tracking have focused on leveraging deep learning. In this paper, we review deep learning approaches for 3D object tracking. We describe key methods in this field and discuss potential future research directions.