• 대한의용생체공학회:의공학회지
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• 제8권2호
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• pp.177-188
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• 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
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.570-574
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• 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
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• 제32B권10호
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• pp.1294-1304
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• 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.

• 제어로봇시스템학회논문지
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• 제7권4호
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• pp.304-308
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• 2001

The increase of video data makes the demand of efficient retrieval, storing, and browsing technologies necessary. In this paper, a video segmentation method (scene change detection method, or shot boundary detection method) for the development of such systems is proposed. For abrupt cut detection, inter-frame similarities are computed using luminance and edge histograms and a cut is declared when the similarities are under th predetermined threshold values. A gradual scene change detection is based on the similarities between the current frame and the previous shot boundary frame. A correlation method is used to obtain universal threshold values, which are applied to various video data. Experimental results show that propose method provides 90% precision and 98% recall rates for abrupt cut, and 59% precision and 79% recall rates for gradual change.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.II
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• pp.279-286
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• 2000

The objective of this research is to detect the papaya fruits on tree in an orchard. The detection of papaya on natural background is difficult because colors of fruits and background such as leaves are similarly green. We cannot separate it from leaves by color information. Therefore, this research will use shape information instead. First, we detect an interested object by detecting its boundary using edge detection technique. However, the edge detection will detect every objects boundary in the image. Therefore, shape description technique will be used to describe which one is the interested object boundary. The good shape description should be invariant in scaling, rotating, and translating. The successful concept is to use Fourier series, which is called "Fourier Descriptors". Elliptic Fourier Descriptors can completely represent any shape, which is selected to describe the shape of papaya. From the edge detection image, it takes a long time to match every boundary directly. The pre-processing task will reduce non-papaya edge to speed up matching time. The deformable template is used to optimize the matching. Then, clustering the similar shapes by the distance between each centroid, papaya can be completely detected from the background.

• 한국전자통신학회논문지
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• 제14권4호
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• pp.663-670
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• 2019

지하철에서 스크린 도어와 플랫폼간의 경계선을 검출할 수 있는 변형된 케니에지 검출 알고리듬을 제안한다. 일반적으로 지하철에서는 플랫폼과 스크린 도어 사이의 경계선은 주변에 비해 어둡게 나타나므로 이의 특성을 고려하여 변형된 bottom-hat 변환을 이용해 에지 영상을 만든다. 이렇게 구한 에지 영상에 이중 문턱화를 통해 강한 에지와 약한 에지를 포함하는 이중 문턱화 영상을 얻는다. 이중 문턱화 영상에 호프 변환을 적용하여 플랫폼과 스크린 도어 간의 경계선을 검출하여 그 길이를 계산하고, 사람 등 물체가 있을 때와 없을 때와의 경계선 길이를 비교함으로써, 경계선을 침범 여부를 판단하는 알고리듬을 제안한다. 본 논문에서는 카메라 높이 위치에 따라 두 종류의 서로 다른 입력영상을 사용하여 제안한 변형된 케니에지 검출 알고리듬에 대한 결과를 컴퓨터 시뮬레이션으로 나타내었다.

• 한국전자통신학회논문지
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• 제13권5호
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• pp.1051-1058
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• 2018

지하철 스크린도어(PSD)에서 발생할 수 있는 안전사고 예방을 위한 영상처리 알고리듬을 제안한다. 우선 지하철 스크린도어 영상에 대해 에지를 검출 하고, 사람의 스크린도어 접근 여부를 판단하기 위해 호프변환을 이용하여 직선을 검출한다. 이를 위해 스크린도어 경계면에 일직선을 긋고 이 직선의 끊김 여부로 사람의 접근을 판단한다. 일반적으로 에지는 영상의 가장 기본적인 특징을 나타내며, 에지 검출은 영상처리 및 컴퓨터 비전 분야에서 매우 중요하다. 에지 검출 방법에는 로버츠, 소벨, 프리윗, 라플라시안 등 고정된 값의 마스크를 사용하는 방법과 영상을 형태학적 관점에서 접근하여 처리하는 모폴로지 방법 및 캐니에지 검출 방법 등이 있다. 본 논문에서는 캐니에지 검출방법과 호프변환을 이용하여 지하철 스크린도어에서 사람의 접근 여부에 대한 감지 알고리듬을 제안하고 실제 그 결과를 컴퓨터 시뮬레이션으로 나타내었다.

• 전자공학회논문지B
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• 제29B권11호
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• pp.111-119
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• 1992

In this paper, we propose an edge detection scheme for noisy images based on the co-occurrence matrix. In the proposed scheme based on the step edge model, the gray level information is simply converted into a bit-map, i.e., the uniform and boundary regions of an image are transformed into a binary pattern by using the local mean. In this binary bit-map pattern, 0 and 1 densely distributed near the boundary region while they are randomly distributed in the uniform region. To detect the boundary region, the co-occurrence matrix on the bit-map is introduced. The effectiveness of the proposed scheme is shown via a quantitative performance comparison to the conventional edge detection methods and the simulation results for noisy images are also presented.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2017년도 추계학술발표대회
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• pp.944-945
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• 2017

Color image edge detection is an important operation in many image processing areas. This paper presents a new method for edge detection based on the Bhattacharyya distance that can handle arbitrary boundaries by exploring several edge patterns. Experiments show promising results compared to some existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권9호
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• pp.2312-2325
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• 2013

In this paper, we propose a preprocessing method that it is to correct the distortion of text area in Korean signboard images as a preprocessing step to improve character recognition. Distorted perspective in recognizing of Korean signboard text may cause of the low recognition rate. The proposed method consists of four main steps and eight sub-steps: main step consists of potential vertical components detection, vertical components detection, text-boundary estimation and distortion correction. First, potential vertical line components detection consists of four steps, including edge detection for each connected component, pixel distance normalization in the edge, dominant-point detection in the edge and removal of horizontal components. Second, vertical line components detection is composed of removal of diagonal components and extraction of vertical line components. Third, the outline estimation step is composed of the left and right boundary line detection. Finally, distortion of the text image is corrected by bilinear transformation based on the estimated outline. We compared the changes in recognition rates of OCR before and after applying the proposed algorithm. The recognition rate of the distortion corrected signboard images is 29.63% and 21.9% higher at the character and the text unit than those of the original images.