• Journal of Biomedical Engineering Research
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• v.25 no.2
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• pp.103-109
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• 2004

A virtual arthroscopy is a simulation of optical arthroscopy that reconstructs anatomical structures from tomographic images in joint region such as a knee, a shoulder and a wrist. In this paper, we propose a virtual arthroscopy based on isosurface raycasting, which is a kind of volume rendering methods for generating 3D images within a short time. Our method exploits a spatial data structure called min-max map to produce high-quality images in near real-time. Also we devise a physically-based camera control model using potential field. So a virtual camera can fly through in articular cavity without restriction. Using the high-speed rendering method and realistic camera control model, we developed a virtual arthroscopy system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2005.11a
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• pp.275-278
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• 2005

본 연구는 디스플레이 제품의 개발 및 생산과정에서 OSD 메뉴문자의 오류 유무를 검사하는 과정을 컴퓨터 비전기술을 사용하여 자동화하는 방법을 제안한다. 디스플레이 제품의 OSD 메뉴는 순차적인 제어과정을 통해서 제한된 디스플레이 영역에 여러 종류의 언어와 기호를 포함하는 형태로 출력된다. 기존의 제품개발 과정에서 이러한 메뉴 항목의 정확성을 검증하는 작업은 작업자의 육안에 의한 판단과 수작업에 의해 이루어지고 있는데, 이는 반복작업에 의한 집중력 저하 및 판단착오에 의한 오류의 가능성을 내재한다. 또한 작업자가 다양한 나라의 언어에 대한 문자형태와 기호표현의 특성을 이해하여야 하고, 검증작업 자체에 따르는 부수적인 시간과 노력을 필요로 한다. 이에 본 연구에서는 디스플레이 제품의 OSD 메뉴와 같이 특수한 구조를 갖는 문서영상에 대한 논리적인 구조분석을 통해서 연속적인 문서영상을 발생시키는 작업스케쥴러를 생성하고, 작업스케쥴러에 의해 순차적으로 발생된 영상문서에 대한 전처리, OSD 메뉴의 기하학적 구조분석 및 문자영역을 추출하는 방법과, 표준패턴 구축 및 원형정합에 의한 문자의 오류를 검증하는 방법과 오류를 관리하는 기법을 제안한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.570-576
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• 2005

Recognition of posed face is one of the most challenging problems in the field of face recognition. In this paper, as a preprocessing step for recognizing such faces, a method to transform non-frontal face images into frontal face images is proposed. The linear relationship between eigenfaces is utilized to obtain a pose transform matrix. The proposed method is verified with a well-known face recognition algorithm based on PCA/LDA. Compared to the conventional algorithm applied to the original posed face images, our experimental results indicated that the proposed method contributes to improve the recognition rate of such faces by $20\%$.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.67-70
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• 2015

최근 깊이 영상 기반 렌더링 방법을 이용하여 제작된 3차원 컨텐츠가 우리의 눈을 즐겁게 해주고 있다. 이러한 깊이 영상 기반 렌더링에서는 필연적으로 색상 카메라와 깊이 카메라 간의 시점 차이가 발생한다. 따라서 두 시점을 일치시키는 전처리 과정으로서 카메라 파라미터가 중요한 역할을 수행한다. 카메라 파라미터를 획득하는 과정으로 카메라 캘리브레이션이 수행된다. 널리 사용되는 기존의 카메라 캘리브레이션 방법은 평면의 체스보드 패턴을 여러 자세로 촬영한 다음 패턴 특징점을 손으로 직접 선택해야하는 불편함이 따른다. 따라서 본 논문에서는 이 문제를 해결하기 위해 원형 샘플 화소 검사와 호모그래피 예측을 이용한 반자동 카메라 캘리브레이션을 제안한다. 제안하는 방법은 먼저 FAST 코너 검출 알고리즘을 이용하여 패턴 특징점의 후보를 영상으로부터 추출한다. 다음으로 원형 샘플 화소를 검사하여 후보군의 크기를 줄인다. 그리고 호모그래피 예측을 통해 손실된 패턴 특징점을 보완하는 완전한 패턴 특징점군을 획득한다. 마지막으로 화소 정확성 향상을 통해 실수 단위의 정확성을 가지는 패턴 특징점의 위치를 획득한다. 실험을 통해 제안하는 방법이 기존의 방법과 비교하여 카메라 파라미터의 정확성은 유지하고 수작업의 불편함을 해소할 수 있음을 확인했다.

• Journal of IKEEE
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• v.7 no.2 s.13
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• pp.271-280
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• 2003

This paper presents an effective method to segment objects from the ultrasound medical image which is inherently corrupted by speckle noise. In order to reduce the speckle noise morphological opening was used as preprocessing. For the preprocessed image, sample variance of neighborhood pixels is to be computed to classify where the pixel is located on the edge region or homogeneous region. Then pseudomedian filtering with different window size is taken according to the region classified, named adaptive pseudomedian filter. Various experimental results were presented to prove superiority of the proposed filter.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.93-96
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• 2000

In this paper, we suggest a feature points selection method using block-based watershed segmentation and polygon approximation for preprocessing of MPEG-4 mesh generation. 2D natural image is segmented by 8$\times$8 or 4$\times$4 block classification method and watershed algorithm. As this result, pixels on the watershed lines represent scene's interior feature and this lines are shapes of closed contour. Continuous pixels on the watershed lines are selected out feature points using Polygon approximation and post processing.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.939-947
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• 2019

With the revitalization of the media market, the necessity of compression, searching, editing and copyright protection of videos is increasing. In this paper, we propose a method to detect scene change in all these fields. We propose a pre-processing, feature point extraction using SIFT, and matching algorithm for detecting the same scene change even if distortions such as resolution change, subtitle insertion, compression, and flip are added in the distribution process. Also, it is applied to filtering technology and it is confirmed that it is effective for all transformations other than considering transform.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.4
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• pp.349-354
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• 2005

The study on computer vision is aimed on creating a system to substitute the ability of human visual sensor. Especially, moving object tracking system is becoming an important area of study. In this study, we have proposed the tracking system of single moving object based on motion estimation. The tracking system performed motion estimation using differential image, and then tracked the moving object by controlling Pan/Tilt device of camera. Proposed tracking system is devided into image acquisition and preprocessing phase, motion estimation phase and object tracking phase. As a result of experiment, motion of moving object can be estimated. The result of tracking, object was not lost and tracked correctly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.437-440
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• 2022

In modern society, the use of the image processing field is increasing rapidly due to the 4th industrial revolution and the development of IoT technology. In particular, edge detection is widely used in various fields as an essential preprocessing process in image processing applications such as image classification and object detection. Conventional methods for detecting an edge include a Sobel edge detection filter, a Roberts edge detection filter, a Prewitt edge detection filter, Laplacian of Gaussian (LoG), and the like. However, existing methods have the disadvantage of showing somewhat insufficient performance of edge detection characteristics in a low-light level environment with low contrast. Therefore, this paper proposes an edge detection algorithm based on contrast analysis to increase edge detection characteristics even in low-light level environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.121-123
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• 2021

Image processing is being used in various forms in important fields of the 4th industrial revolution, such as artificial intelligence, smart factories, and the IoT industry. In particular, in systems that require data processing such as object tracking, medical images, and object recognition, noise removal is used as a preprocessing step, but the existing algorithm has a drawback in that blurring occurs in the filtering process. Therefore, in this paper, we propose a filter algorithm using switching fuzzy weights. The proposed algorithm switches the fuzzy function by dividing the low-frequency region and the high-frequency region by the standard deviation of the filtering mask, and obtains the final output according to the fuzzy weight. The proposed algorithm showed improved results compared to the existing method, and showed excellent characteristics in the region where the high-frequency component is strong.