• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.5
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• pp.559-565
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• 1988

A new valley operator is presented for extracting sketch features which contain valleys and edges subject to local intensities. It is a very simple operator using the local probablities in a 3x3 local window. Experimental results show its excellent performance over the existing valley or edge operators.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.14 no.1
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• pp.111-118
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• 1996

In this paper, topographic edge points are detected from digital elevation model. Topographic edge points can be considered as the points which have rapid variation from its neighborhood. In this study, these points are dotected by Laplacian operator and noise reduction system is applied to remove small ripple. The results of this study show that Laplacian operator detects efficiently the topographic edge points, and that noise reduction system by local variance is efficient to remove small ripple but inefficient to reconstruct topographical features.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.7
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• pp.709-718
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• 1992

A new edge detection operator superimposing two displaced Gaussian smoothing filters Is proposed as an approximate operator for the DroG(flrst derivative of Gaussian) known as a sub-op-timal step edge detector. The performance of the proposed edge detector Is very close to that of the DroG with the performance criteria . signal to noise ratio, locality, and multiple response. And the computational complexity can be reduced almost by a half of that of DroG, because of the use of common 2-D smoothing filter for DroG and LoG ( Laplacian of Gausslan) systems.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.99-106
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• 2009

Though edge detection, an important stage that significantly affecting the performance of image recognition, has been given numerous researches on its execution methods, it still remains as difficult problem and it is one of the components for image recognition applications while it is not the only way to identify an object or track a specific area. This paper, unlike gradient operator using edge detection method, found out edge pixel by referring to 2 neighboring pixels information in binary image and comparing them with pre-defined 4 edge pixels pattern, and detected binary image edge by determining the direction of the next edge detection exploring pixel and proposed method to detect binary image edge by repeating step of edge detection to detect another area edge. When recognizing image, if edge is detected with the use of gradient operator, thinning process, the stage next to edge detection, can be omitted, and with the edge detection algorithm executing time reduced compared with existing area edge tracing method, the entire image recognizing time can be reduced by applying real-time image recognizing system.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1337-1345
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• 1996

Edge detection is the first step and very important step in image nalyisi. In this paper, proposed edge detection algorithm based on informations of edge structures and it is different from other classical edge detection operators such asgradient and surface fitting algorithm. The firs, we defined characteristics of edge structures such as continuity, thinness, localization, length. The second, we defined valid edge structures and ideal edge pixel positions in $3\times3$ window based on edge characteristics of edge structures. And we proposed twelve windows for enhance dissimilarity regions based on valid edge structures and ideal edge pixel positions. In specially, proposed algorithm was shown better performance of edge detection than other operators such as gradient operator and the LoG(Laplacian of gradient) operator of zero crossings in noisy test image with $\sigma=30$.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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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.

• Journal of Biomedical Engineering Research
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• v.8 no.2
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.141-147
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• 2000

In the restoration of degraded noisy motion blurred image, we have trade-off problem between smoothing the noise and restoration of the edge region. While the noise is smoothed, die edge or details will be corrupted. On the other hand, restoring the edge will amplify the noise. To solve this problem we propose an adaptive algorithm which uses I- H regularization operator for flat region and Laplacian regularization operator for edge region. Through the experiments, we verify that the proposed method shows better results in the suppression of the noise amplification in flat region, introducing less ringing artifacts in edge region and better ISNR than those of the conventional ones.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.7-21
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• 2019

In order to improve the edge segmentation effect of the level set image segmentation and avoid the influence of the initial contour on the level set method, a saliency level set image segmentation model based on local Renyi entropy is proposed. Firstly, the saliency map of the original image is extracted by using saliency detection algorithm. And the outline of the saliency map can be used to initialize the level set. Secondly, the local energy and edge energy of the image are obtained by using local Renyi entropy and Canny operator respectively. At the same time, new adaptive weight coefficient and boundary indication function are constructed. Finally, the local binary fitting energy model (LBF) as an external energy term is introduced. In this paper, the contrast experiments are implemented in different image database. The robustness of the proposed model for segmentation of images with intensity inhomogeneity and complicated edges is verified.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.96-99
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• 1996

본 연구는 CAD/CAM에서 3차원 물체를 표현하는 기법중 하나인 Solid Modeling을 구성하는 데이터 구조를 객체지향화 함으로써 보다 효율적이고 유연한 설계개발환경을 제공하고자 한다. 이를 위해서 가장 일반적으로 Solid Modeling을 표현하는 데이터 구조인 기존의 Half-Edge Data Structure를 기본모델로 하여 점(Vortex), 선(Edge), 면(Face), 입체(Solid)를 객체 Class로 하고 Euler Operator를 Method로 하는 객체지향 반모서리 데이터 구조(Object Oriented Half-Edge Data Structure)를 개발하였다.