• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.704-706
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• 2003

본 논문에서는 3차원 그래픽 데이터베이스를 위한 효과적인 질의 처리 시스템을 제안한다. 이 질의 처리 시스템은 3차원 그래픽 객체나 3차원 이미지 객체(이하 3D 객체)에 대한 모양 특징 기반(feature-based) 질의를 지원한다. 제안하는 시스템은 3D 객체 에 대한 특징 중 모양 모양에 초점을 맞춘다. 객체간의 유시도 검색을 위해 객체의 모양 특징은 단순화되고 추상화 되어 사용된다. 3D 객체 데이타베이스 구성을 위해 XML을 확장한 3DGML 시스템을 이용하고 질의 처리 언어로는 XML-QL을 이용한다. 본 논문에서 제안하는 질의 처리 시스템은 3D 객체를 포함한 멀티미디어 데이터의 효율적인 검색에 활용될 수 있으며 다양한 그래픽 응용 분이 등에서 활용될 수 있을 것이다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.108-110
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• 2010

최근 3D 비디오 서비스에 대한 관심이 고조되고 있는 가운데, 지상파 DMB 및 위성 DMB에서도 스테레오스코픽 비디오 서비스를 제공하기 위한 노력이 진행되고 있다[1]-[3]. DMB-AF 파일 포맷[4]은 MPEG에서 제정한 DMB 파일 포맷 국제 표준이다. 이 표준 제정 당시에는 스테레오스코픽 비디오 콘텐트를 지원하는 기능이 들어 있지 않았다. 본 논문에서는 DMB-AF 한 파일 내에서 2D 비디오, BIFS에 의해 스테레오스코픽 이미지가 오버레이된 2D 비디오, 스테레오스코픽 비디오 등이 시간적으로 혼용될 수 있는 방법을 제안한다. 또한 이 방법은 기존 2D 비디오의 재생만 지원하는 기존 DMB-AF 플레이어와의 호환성을 보장한다. 따라서 기존 DMB-AF 플레이어가 BIFS에 의해 스테레오스코픽 이미지가 오버레이된 2D 비디오 또는 스테레오스코픽 비디오가 포함된 DMB-AF 파일을 재생할 때에는 2D 이미지 또는 2D 비디오로 재생할 수 있다. 제안한 방법은 한 프레임을 좌우로 반으로 나누어 좌안 및 우안 비디오를 좌우로 배치한 화면분할(side-by-side) 포맷에 의한 스테레오스코픽 비디오뿐만 아니라 좌안 또는 우안 비디오 중 하나는 2D 재생용의 기준 비디오로 다른 하나는 스테레오스코픽 비디오를 위한 부가 비디오로 사용하는 기본 포맷에 의한 스테레오스코픽 비디오도 지원한다. 후자의 경우, 부가 비디오는 가로 해상도가 기준 비디오의 1/2인 선택사항 포맷도 지원한다. 스테레오스코픽 비디오를 지원하기 위해, 기존 DMB-AF 표준의 확장을 최소화하는 방법을 제안한다.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.61-67
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• 2017

Recently, CCTV has been combined with areas such as big data, artificial intelligence, and image analysis to detect various abnormal behaviors and to detect and analyze the overall situation of objects such as people. Image analysis research for this intelligent video surveillance function is progressing actively. However, CCTV images using 2D information generally have limitations such as object misrecognition due to lack of topological information. This problem can be solved by adding the depth information of the object created by using two cameras to the image. In this paper, we perform background modeling using Mixture of Gaussian technique and detect whether there are moving objects by segmenting the foreground from the modeled background. In order to perform the depth information-based segmentation using the RGB information-based segmentation results, stereo-based depth maps are generated using two cameras. Next, the RGB-based segmented region is set as a domain for extracting depth information, and depth-based segmentation is performed within the domain. In order to detect the center point of a robustly segmented object and to track the direction, the movement of the object is tracked by applying the CAMShift technique, which is the most basic object tracking method. From the experiments, we prove the efficiency of the proposed object detection and tracking method using the RGB-D model.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.859-864
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• 2006

Mean shift 는 데이터의 특징을 잘 살려내는 None-parametric 방법으로, 특히 영상처리분야에서 많은 각광을 받아왔다. 하지만 좋은 결과를 보장하는 뛰어난 성능에도 불구하고, 높은 메모리소요와 긴 처리시간에 기인하여, 비디오처리 등의 분야에 적용하기엔 현실적인 제약점이 있다. 상기한 제약점을 극복하기 위해, 본 시스템은 비디오를 분석하여 전경과 후경으로 나눈다. 본 논문은 전경으로 분류된 부분에 대해 각 분리된 개체를구분하고, 좌표변환(coordinate shift)을 실행하여 연산을 할 비디오의 연산의 규모를 줄이는 방법론을 제시한다. 이러한 처리로 매우 많은 처리시간이 단축됨을 실험을 통해 알 수 있었다. 다음으로, 나뉘어진 전경에 3D mean shift를 적용하여 생성된 결과물에 대하여 3D cluster data structure 를 생성하고, 이를 이동하여 인터랙티브 에디팅이 가능하도록 하였다. 후경으로 나뉜 데이터는 이미지 한 장으로 축약이 되며, 2D mean shift 기반의 interactive cartooning system 을 통하여 만화화가 된다. 본 논문은 만화 특유의 단순한 톤을 표현하기 위해, 세밀한 분할이 필요한 부분과 그렇지 않은 부분을 따로 구분하여 처리하는 레이어처리방법을 제안한다. 위의 과정을 여러 실사이미지에 적용, 실험해본 결과 기존의 연구결과에 비해 매우 짧은 시간 내에 대상의 특징이 잘 나타낸 양질의 결과물이 생성되었다. 이러한 결과물은 출판, 영상편집분야 등 여러 분야에서 요긴하고 간편하게 사용될 수 있을 것으로 생각된다.

• Journal of Service Research and Studies
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• v.5 no.2
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• pp.103-110
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• 2015

Recently, Classification of characters in a 3D FPS game has emerged as a very significant issue. In this study, We propose the game character Classification method using Image Region Segmentation of the extracting meaningful object in a simple operation. In this method, first used a non-linear RGB color model and octree color quantization scheme. The input image represented a less than 20 quantized color and uses a small number of meaningful color histogram. And then, the image divided into small blocks, calculate the degree of similarity between the color histogram intersection and adjacent block in block units. Because, except for the block boundary according to the texture and to extract only the boundaries of the object block. Set a region by these boundary blocks as a game object and can be used for FPS game play. Through experiment, we obtain accuracy of more than 80% for Classification method using each feature. Thus, using this property, characters could be classified effectively and it draws the game more speed and strategic actions as a result.

• 한국가시화정보학회:학술대회논문집
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• 2006.12a
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• pp.96-101
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• 2006

3-D visualization using confocal laser scanning microscopy (CLSM) in a chaotic micromixer was performed as a reproduction experiment and the feasibility of 3-0 imaging technique in the microscale was confirmed. For diagonal micromixer (DM) and two types of staggered herringbone micromixers (SHM) designed by Whitesides et al., to verify the evolution of mixing, cross sectional images are reconstructed at the end of every cycle. In a DM, clockwise rotational flow motion generated by diagonal ridges placed on the floor of micromixer is observed and this motion makes the fluid commingle. On the contrary, there are two rotational flow structures in the SHM and the centers of rotation exchange their position each other every half cycle because of the V shape of ridges varying their orientation every half cycle. Local rotational flow and local extensional flow generated by the complicate ridge pattern make the flow be chaotic and accelerate the mixing of fluid. The dominant parameter that influences on the mixing characteristic of SHM is not the length of micromixer but the number of ridges under the same flow configurations.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.24-35
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• 2016

By estimating environment light distribution, we can generate realistic shadow images in AR(augmented reality). When we estimate light distribution without sensing equipment, environment light model, geometry of virtual object, and surface reflection property are needed. Previous study using 3D marker builds surrounding light environment with a geodesic dome model and analyzes shadow images. Because this method employs candidate shadow maps in initial scene setup, however, it is difficult to estimate precise light information. This paper presents a novel light estimation method based on hierarchical light distribution model subdivision. By using an overlapping area ratio of the segmented shadow and candidate shadow map, we can make hierarchical subdivision of light geodesic dome.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.563-572
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• 2024

Image processing and computer vision technologies are becoming increasingly important in a variety of application fields that require techniques and tools for sophisticated image analysis. In particular, image segmentation is a technology that plays an important role in image analysis. In this study, in order to identify recent research trends on image segmentation techniques, we used the Web of Science(WoS) database to analyze the R&D topography based on the network structure of the author's keyword co-occurrence matrix. As a result, from 2015 to 2023, as a result of the analysis of the R&D map of research articles on image segmentation, R&D in this field is largely focused on four areas of research and development: (1) researches on collecting and preprocessing image data to build higher-performance image segmentation models, (2) the researches on image segmentation using statistics-based models or machine learning algorithms, (3) the researches on image segmentation for medical image analysis, and (4) deep learning-based image segmentation-related R&D. The scientometrics-based analysis performed in this study can not only map the trajectory of R&D related to image segmentation, but can also serve as a marker for future exploration in this dynamic field.

• Journal of the Korean Institute of Landscape Architecture
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• v.15 no.1
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• pp.39-67
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• 1987

The purpose of this thesis is to suggest objective basic data for the environmental design through the quantitative analysis of the visual quality included in the physical environment of forest landscape. For this, landscape values of forest landscape have been evaluated by using the Iverson method, the images structure of forest landscape's main utilizing space have been analysed by the factor analysis algorithm, degree of visual preferences have been pleasured mainly by questionnaries and SBE method, and finally these thesis can be summarized as fallow LCP with high values of Iverson factors I and IV yield high landscape value. Specifically, Iverson factor IV has been found to play the dominant. For all experimental points, significant seasonal variations in S.D. scale values have been observed. In natural parks, where artificial structures are complementary to the natural landscape, main factors of image are S.D. scales such as the visual sequence, the formal simplicity of structures, the emphasis, the unification of heterogeneous factors and the assimilation. Factors covering the spatial image of natural parks have been found to be the overall evaluation, the individual characteristics, the tidiness, the potentiality, the dignity, the intimacy and the space volume. For all seasons, factors such as the individual characteristics, the dignity, the tidiness, the potentiality, yield high factor scores. As for factors determining the degree of visual preference, variables such as the summit, the skyline, rocks, the water and the degree of natural destruction by artificial structures yield high values for all seasons.

• Journal of the Korea Society of Computer and Information
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• v.27 no.4
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• pp.27-36
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• 2022

In this paper, to improve the conditions of the fish processing site, we propose a method to predict the cutting point of fish according to the target weight using AI machine vision. The proposed method performs image-based preprocessing by first photographing the top and front views of the input fish. Then, RANSAC(RANdom SAmple Consensus) is used to extract the fish contour line, and then 3D external information of the fish is obtained using 3D modeling. Next, machine learning is performed on the extracted three-dimensional feature information and measured weight information to generate a neural network model. Subsequently, the fish is cut at the cutting point predicted by the proposed technique, and then the weight of the cut piece is measured. We compared the measured weight with the target weight and evaluated the performance using evaluation methods such as MAE(Mean Absolute Error) and MRE(Mean Relative Error). The obtained results indicate that an average error rate of less than 3% was achieved in comparison to the target weight. The proposed technique is expected to contribute greatly to the development of the fishery industry in the future by being linked to the automation system.