• 대한의용생체공학회:의공학회지
• /
• 제8권2호
• /
• pp.177-188
• /
• 1987

Detection of left ventricular boundary for the functional analysis of LV(left ventricle) is obtained using automatic boundary detection algorithm based on dynamic program ming method. This scheme reduces the edge searching time and ensures connective edge detection, since it does not require general edge operator, edge thresholding and linking process of other edge detection methods. The left ventricular diastolic volume and systolic volume were computed after this automatic boundary detection, and these volume data were applied to analyze LV ejection fraction.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
• /
• pp.570-574
• /
• 1990

Detection of left ventricular boundary for the functional analysis of LV(left ventricle)is obtained using automatic boundary detection algorithm based on dynamic programming method. This scheme reduces the edge searching time and ensures connective edge detection, since it does not require general edge operator, edge thresholding and linking process of other edge. detection methods. The left ventricular diastolic volume and systolic volume and systolic volume were computed after this automatic boundary detection, and these Volume data wm applied to analyze LV ejection fraction.

• 전자공학회논문지B
• /
• 제32B권10호
• /
• pp.1294-1304
• /
• 1995

In this paper, a method has been proposed for the fully automatic detection of left ventricular endocardial boundary in B-mode short axis echocardiography without manual intervention by human operator. The proposed method makes use of the weighted model that approximates to endocardium and incomplete edge information for echocardiography. Therefore, this method is more effective than boundary detection by only edge information. The implementation of this method is as follows. First, the proposed algorithms are used in order to detect the approximate boundary, then a weighted model with the approximate boundary is constructed. Finally, the cavity center of the left ventricle performing the Hough transform with the weighted model and edge image can be found automatically, and then the endocardial boundary using detected center, original image, weighted model, and edge image can be detected. validations of this method with experimental results on echo image of dog's heart and clinical echocardiography is verified.

• 대한의용생체공학회:의공학회지
• /
• 제11권2호
• /
• pp.217-226
• /
• 1990

This paper presents a new algorithm that extracted lung region in X-ray and enhanced the region. With a lung region that was extracted by histogram threshold value, it was diffi cult to detect perfect lung boundary. Therefore we presented perfect lung boundary detection method using apex detection and apex region restoration. Also, by applying modified equalization algorithm and presented function to inside of lung region, we want to give help to automatic diagnosis In X-ray chest image. Presented main line trace algorithm gave good result in detection of lung boundary And, as apex detection method using lung row and column gray level average value found more correct place of lung than the rpethod of prior algorithm, we succeeded perfect lung region detection, Also, presented function that had lung region's gray level distribution characteristic was very effective to image enhancement.

• Journal of the Korean Data and Information Science Society
• /
• 제19권4호
• /
• pp.1297-1304
• /
• 2008

This paper proposes a machine learning approach for language-independent sentence boundary detection. The proposed method requires no heuristic rules and language-specific features, such as part-of-speech information, a list of abbreviations or proper names. With only the language-independent features, we perform experiments on not only an inflectional language but also an agglutinative language, having fairly different characteristics (in this paper, English and Korean, respectively). In addition, we obtain good performances in both languages. We have also experimented with the methods under a wide range of experimental conditions, especially for the selection of useful features.

• 방송공학회논문지
• /
• 제7권2호
• /
• pp.107-113
• /
• 2002

본 논문에서는 자동으로 야구 비디오를 요약하는 방법과 이를 구현한 소프트웨어 시스템을 제안한다. 제안된 시스템은 빠른 수행 속도와 정확성 높은 요약 결과를 추구한다. 이를 위해 압축비디오상의 특징 값에 기반 한 빠른 비디오 분할과 간단한 자막 인식을 수행하여 야구 경기에서 중요한 이벤트들을 검출한다. 또한, 본 시스템은 여러 레벨의 비디오 요약을 지원하기 위해 계층적 구조의 내용 기술을 지원한다.

• 대한의용생체공학회:의공학회지
• /
• 제17권1호
• /
• pp.109-120
• /
• 1996

Cardiac function is evaluated quantitatively using angiographic images via the analysis of the shape change or the heart wall boundaries. To kin with, boundary defection or ESLV(End Systolic Lert Ventricular) and EDLV(End Diastolic Left Ventricular) is essential for the quantitative analysis of cardiac function. The boundary detection methods proposed in the past were almost semi-automatic. Intervention by a knowledgeable human operator was still required Of con, manual tracing of the boundaries is currently used for subsequent analysis and diagnosis. This method would not cut excessive time, labor, and subjectivity associated with manual intervention by a human operator. EDLV images have noncontiguous and ambiguous edge signal on some boundary regions. In this paper, we propose a new method for automated detection of boundaries in noncontiguous and ambiguous EDLV images. The boundary detection scheme which based on a priori knowledge information is divided into two steps. The first step is to detect the candidate edge points of EDLV using ESLV boundaries. The second step is to correct detected boundaries of EDLV using the LV shape. We developed the algorithm of modifying EDLV boundaries defined adaptive modifier. We experimented the method proposed in this paper and compared our proposed method with the manual method in detecting boundaries of EDLV. In the areas within estimated boundaries of EDLV, the percentage of error was about 1.4%. We verified the useflilness and obtained the satisfying results througll the experiments of the proposed method.

• 한국의학물리학회지:의학물리
• /
• 제7권2호
• /
• pp.79-90
• /
• 1996

본 논문에서는 2 차원 심초음파도의 경계선 유사 영역에 대해 베이즈 추정기를 사용하여 경계선 검출을 위한 자동문턱 결정방법을 제안하고자 한다. 경계선 유사영역은 전처리과 정에서 흐려진 영상을 명확히 하는데 사용할 열비등방성 확산 방법의 전도계수로부터 얻어진다, 이러한 경계선 유사 영역에 대해 최적 문턱치를 선택하기 위해 베이즈 추정기가 사용되었다. 이 문턱치를 사용하여 영상을 이진화함으로서 심초음파도의 경계선을 자동 적으로 검출하게 된다. 마지막으로 본래의 심초음파도에 위에서 얻어진 경계선을 덧씌움으로써 경계선이 강조된 심초음파도를 얻을 수 있게 된다.

• 대한전자공학회논문지SP
• /
• 제41권6호
• /
• pp.99-108
• /
• 2004

본 논문에서는 CCD(charge-coupled device) 영상 기반의 자동 표적 탐지 시스템(ATD System : Automatic Target Detection System)에 적합한 빠른 탐색 방법을 제안한다. 무기체계에서의 활용을 위해서는 빠른 연산이 주요한 변수인 만큼 이 논문에서는 적은 계산량으로 다양한 표적을 탐지할 수 있는 능력에 주안점을 두고 있다. 표적 훈련(train)단계에서는 구간별 수직 방향 프로젝션을 이용하여 1D의 템플릿을 구성하고 K-means clustering과 이진 트리 구조(binary tree structure)를 활용하여 실제 시험 단계에서 템플릿 정합하는 횟수를 최소화한다. 또한 Correlation-based Adaptive Predictive Search(CAPS)를 이용하여 각각의 템플릿에 적응적인 skip-width를 사용하여 탐색 속도를 높이고 클러터 제거 단계에서는 윤곽선으로부터 추출한 Fourier Descriptor계수를 비교함으로써 초기 탐지에서 타겟으로 오인된 클러터를 모양 정보에 기반해서 제거하는 방법을 사용한다.

• 전자공학회논문지B
• /
• 제28B권10호
• /
• pp.842-913
• /
• 1991

The automatic target detection which automatically identifies the location of the target with its input image is one of the significant subjects of image processing field. Then, there are some problems that should be solved to detect the target automatically from the input image. First of all, the ambiguity of the boundary between targets or between a target and background should be solved and the target should be searched adaptively. In other words, the target should be identified by the relative brightness to the background, not by the absolute brightness. In this paper, to solve these problems, a new algorithm which can identify the target automatically is proposed. This algorithm uses the set of fuzzy for solving the ambiguity between the boundaries, and using the weight according to the brightness of data in the input image, the target is identified adaptively by the relative brightness to the background. Applying this algorithm to real images, it is experimentally proved that it is can be effectively applied to the automatic target detection.