• 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.

• 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 the Korean Institute of Telematics and Electronics B
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• v.32B no.10
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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.

• Journal of Biomedical Engineering Research
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• v.11 no.2
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• pp.217-226
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• 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
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• v.19 no.4
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• pp.1297-1304
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• 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.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.107-113
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• 2002

In this paper, we propose a method and a software system for automatic summarization of baseball game videos. The proposed system pursues fast execution and high accuracy of summarization. To satisfy the requirement, the detection of important events in baseball video is performed through DC-based shot boundary detection algorithm and simple caption recognition method. Furthermore, the proposed system supports a hierarchical description so that users can browse and navigate videos in several levels of summarization. In this paper, we propose a method and a software system for automatic summarization of baseball game videos. The proposed system pursues fast execution and high accuracy of summarization. To satisfy the requirement, the detection of important events in baseball video is performed through DC-based shot boundary detection algorithm and simple caption recognition method. Furthermore, the proposed system supports a hierarchical description so that users can browse and navigate videos in several levels of summarization.

• Journal of Biomedical Engineering Research
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• v.17 no.1
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• pp.109-120
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• 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.

• Progress in Medical Physics
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• v.7 no.2
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• pp.79-90
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• 1996

In this paper, we present an automatic threshold decision method to detect the contour of the a 2-D echocarodiogram by using the Bayes estimator for the boundary-like region. The boundary-like region is constructed from the conduction coefficient of the heat anisotro-pic diffusion method which enforces the blurred image during the preprocessing step. For the boundary-like region, we used the Bayes estimator to select an optimal threshold level. From this threshold value, the contour of the echocardigrams can be detected automatically Finally by overlapping the estimated contour to the original echocardiogram, we can obtain the contour enforced ultrasound echocardiogram.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.99-108
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• 2004

In this paper, a new fast detection and clutter rejection method is proposed for CCD-image-based Automatic Target Detection System. For defence application, fast computation is a critical point, thus we concentrated on the ability to detect various targets with simple computation. In training stage, 1D template set is generated by regional vertical projection and K-means clustering, and binary tree structure is adopted to reduce the number of template matching in test stage. We also use adaptive skip-width by Correlation-based Adaptive Predictive Search(CAPS) to further improve the detecting speed. In clutter rejection stage, we obtain Fourier Descriptor coefficients from boundary information, which are useful to rejected clutters.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.10
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• pp.842-913
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• 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.