• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.392-399
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• 2010

The Automobile has developed and changed through the years from the invention and increased human-being's scope of activity. Junction Box, one of the part of automobile, is inspected by human eyes which caused mistakes and slow progress. To achieve the speed and accuracy the system was compensated by vision system which is inspecting automatically. This paper is automatic inspection of fuse and relay which is inserted in the junction box by checking the color and pattern of the cover. After checking the performance of the system by using the junction box, the result was 100 percent perception and open the possibility to inspect junction box fast and easy and accurate if it is applied to the industry.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.363-366
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• 2001

The present process of grading leather quality by the rare eyes is not reliable. Because inconsistency of grading due to eyes strain for long time can cause incorrect result of grading. Therefore it is necessary to automate the process of grading quality of leather based on objective standard for it. In this paper, leather automatic classification system consists of the process obtaining the information of leather and the process grading the quality of leather from the information. Leather is graded by its information such as texture density, types and distribution of defects. This paper proposes the algorithm which sorts out leather information like texture density and defects from the gray-level images obtained by digital camera. The density information is sorted out by the distribution value of Fourier spectrum which comes out after original image is converted to the image in frequency domain. And the defect information is obtained by the statistics of pixels which is relevant to Window using searching Window after sort out boundary lines from preprocessed images. The information for entire leather is used as standard of grading leather quality, and the proposed algorithm is practically applied to machine vision system.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.39-46
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• 2015

This paper presents an automatic method to detect and count the cells from microorganism images based on mobile environments. Cell counting is an important process in the field of biological and pathological image analysis. In the past, cell counting is done manually, which is known as tedious and time consuming process. Moreover, the manual cell counting can lead inconsistent and imprecise results. Therefore, it is necessary to make an automatic method to detect and count cells from biological images to obtain accurate and consistent results. The proposed multi-step cell counting method automatically segments the cells from the image of cultivated microorganism and labels the cells by utilizing topological analysis of the segmented cells. To improve the accuracy of the cell counting, we adopt watershed algorithm in separating agglomerated cells from each other and morphological operation in enhancing the individual cell object from the image. The system is developed by considering the availability in mobile environments. Therefore, the cell images can be obtained by a mobile phone and the processed statistical data of microorganism can be delivered by mobile devices in ubiquitous smart space. From the experiments, by comparing the results between manual and the proposed automatic cell counting we can prove the efficiency of the developed system.

• Journal of KIISE:Software and Applications
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• v.35 no.12
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• pp.753-763
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• 2008

The amount of UCCs (User Created Contents) has been increasing rapidly and is associated with a serious copyright problem. Automatic logo detection in videos is an efficient means of overcoming the copyright problem. However, logos have varying characteristics, which make logo detection and recognition very difficult. Especially, there are frequent logo transitions in a video, comprising several video contents. This disrupts accurate video segmentation based on logos. Therefore, this paper proposes an accurate logo transition detection method for recognizing logos in digital video contents. The proposed method accurately segments a video according to logo and efficiently recognizes various types of logos. The experimental results demonstrate the effectiveness of the proposed method for logo detection and video segmentation according to logo.

• Journal of Biomedical Engineering Research
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• v.20 no.1
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• pp.69-73
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• 1999

In this paper, an algorithm based on Snakes is proposed to detect the boundary of 3D images. From the first-slice MR image, the boundary of an object is detected manually. The detected boundary points are used as initial control points for detecting the boundary of the next MR image. To detect the boundary from the rest of MR images automatically, an energy term using spatial correlation between adjacent images is added to the Greedy Snakes energy formulation. A measure of shape similarity called BMD was used to evaluate the accuracy of the proposed algorithm. The average BMD value for the proposed algorithm's result is higher than Greedy algorithm's showing the utility of the proposed method.

• Journal of KIISE
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• v.43 no.4
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• pp.404-410
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• 2016

Automated road map generation poses significant research challenges since GPS-based navigation systems prevail in most general vehicles. This paper proposes an automated detecting method for intersection points using GPS vehicle trajectory data without any background digital map information. The proposed method exploits the fact that the trajectories are generally split into several branches at an intersection point. One problem in previous work on this intersection detecting is that those approaches require stopping points and direction changes for every testing vehicle. However our approach does not require such complex auxiliary information for intersection detecting. Our method is based on partial trajectory matching among trajectories since a set of incoming trajectories split other trajectory cluster branches at the intersection point. We tested our method on a real GPS data set with 1266 vehicles in Gangnam District, Seoul. Our experiment showed that the proposed method works well at some bigger intersection points in Gangnam. Our system scored 75% sensitivity and 78% specificity according to the test data. We believe that more GPS trajectory data would make our system more reliable and applicable in a practice.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.437-439
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• 2011

본 논문에서는 카메라에서 입력되는 영상에서 객체의 특징 자동 추출하고 모바일 기기로 전송하여 인체의 움직임을 표현하는 시스템을 제안한다. 제안시스템은 연속된 입력영상에서 인체의 실루엣과 조인트를 자동추출하고 조인트를 추적함으로 객체를 추적한다. 추출된 특징은 객체의 각 연결점의 위치정보로 사용되며 특징을 중심으로 블록매칭 알고리즘을 적용하여 특징의 위치정보를 추적하고 모바일기기로 정보를 전송한다. 모바일 기기에서는 전송된 조인트 정보를 이용하여 인체의 움직임을 재현한다. 제안방법을 실험 동영상에 적용한 결과 인체의 실루엣과 조인트를 자동 검출하며 추출된 조인트로 인체의 매핑이 효율적으로 이루어졌다. 또한 조인트의 추적이 매핑된 인체에 반영되어 인체의 움직임도 적절히 표현되었다.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.1
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• pp.43-52
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• 1999

현재 사용하는 순차적인 뉴스 비디오 검색 방법은 많은 시간을 소비한다는 문제점을 가지고 있다. 따라서 , 본 논문에서는 이러한 문제점을 해결하기 위해서 뉴스 비디오를 내용(뉴스 사건)단위별로 검색할수 있는 자동 인덱스 모듈과 원격 검색 브라우저 모듈을 제시한다. 인덱싱 모듈은 기본적으로 이미지 프로세싱을 기반으로 하여 뉴스 앵커를 검출하고 뉴스 아이템을 분할한다. 인덱싱 구성요소는 뉴스 비디오 내용에 대한 대표영상(뉴스아이콘)과 부가적인 정보를 포함하는 뉴스 자막으로 구성하였다. 검색 브라우저 모듈은 추출된 인덱싱 요소를 아이콘하여 뉴스사건 단위로 내용을 검색할수 있도록 설계하였다. 본 연구의 결과는 매일 발생되는 뉴스를 자동 인덱싱하여 사용자에게 뉴스서비스의 효율적인 적용이 기대된다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.137-140
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• 2019

본 논문에서는 자동 제어 시스템의 이상행위를 분석하기 위하여 MODBUS 프로토콜 기반의 제어 명령을 수집 분류하여 등록된 화이트리스트 기반으로 이를 탐지하는 시스템을 구현하였다. 구현 시스템은 자동 제어 시스템 기반으로 다양한 생산설비를 동작시키는 스마트팩토리 시스템을 비롯하여 국가기간 산업에 활용 가능하며, 생산설비의 이상 작동을 확인하기 위하여 생산설비의 동작 신호를 주기적으로 수집 분석하여 정상적인 작업형태에서 벗어나는 이상 작업을 판단할 수 있도록 구성하였다. 또한, 소형화된 공장 자동화 설비를 구성하여 실제 스마트팩토리 환경에서 제어명령을 수집하고, 수집된 신호로부터 이상 작동을 검출하는 제안 시스템의 구현 결과를 설명한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.601-604
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• 2007

In this paper dose a laver surface check using a real time image process. This system does false retrieval of a laver at a laver production line. At first, a laver image was read in real time using a CCD camera. In this paper, we use an area scan CCD camera. Image is converted into a binary code image using a high-speed imaging process board afterwards. A laver feature is extracted by a binary code image. Surface false retrieval is finally executed using a laver feature. In this paper, we use an area feature of a laver image.