• Journal of the Korean Society for Precision Engineering
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• v.16 no.5 s.98
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• pp.48-57
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• 1999

Applications of thresholding technique are based on the assumption that object and background pixels in a digital image can be distinguished by their gray level values. For the segmentation of more complex images, it is necessary to resort to multiple threshold selection techniques. This paper describes a new method for multiple threshold selection of gray level images which are not clearly distinguishable from the background. The proposed method consists of three main stages. In the first stage, a probability distribution function for a gray level histogram of an image is derived. Cluster points are defined according to the probability distribution function. In the second stage, fuzzy partition matrix of the probability distribution function is generated through the fuzzy clustering process. Finally, elements of the fuzzy partition matrix are classified as clusters according to gray level values by using max-membership method. Boundary values of classified clusters are selected as multiple threshold. In order to verify the performance of the developed algorithm, automatic inspection process of ball grid array is presented.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.50-56
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• 2011

This paper proposes 3D visualization method of compound knowledge which will be able to identify and search easily compound knowledge objects based the multidimensional relationship. For this, we structurized a compound knowledge with link and node which become the semantic network. and we suggested 3D visualization method using SOM. Also, to arrange compound knowledge from 3D space and to provide the chance of realistic and intuitional information retrieval to the user, we proposed compound knowledge 3D clustering methods using object similarity. Compound knowledge 3D visualization and clustering using SOM will be the optimum method to appear context of compound knowledge and connectivity in space-time.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06d
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• pp.139-141
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• 2006

무선 센서 네트워크에서 이벤트 영역을 탐지하는데 있어 이동성을 가진 target objects의 첫 boundary information을 탐지하는 것도 중요하지만 탐지 후 변화하는 boundary information을 지속적으로 반영하는 것 또한 매우 중요하다. 따라서 본 논문에서는 boundary information의 지속적인 반영방법에 대해, Event의 발생빈도수에 따른 clustering update 모델링과 특정 상황에 따른 cluster를 재구성해야 하는 방안을 비교 분석한 후 이에 대한 클러스터링의 에너지 효율적인 방법에 대해서 제안하고 있다.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.1-7
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• 2002

In this paper, it will be supplied to the representation of event abstraction which is useful for understanding information relationship of the object-oriented programs. And the clustering concept with the events will be applied to abstract the events. By clustering the events, user can set the information about the function of the classes and the retrieval of the class library.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.4
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• pp.309-321
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• 1988

This paper proposes on the algorithm of axis equation & radius function for the G.C representation which describes the curved objects with circular cross section. Object combined with linear and nonlinear parts is detached by clustering from depth data & axis points is extracted by normal vecter of the surface mask patches. In ths case of nonlinear axis point, axis equation is described by Hermite curve & the effectiveness of this paper is demonstrated by serveral experiments.

• Smart Media Journal
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• v.1 no.4
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• pp.27-34
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• 2012

In this paper, a novel text binarization is presented that can deal with some complex conditions, such as shadows, non-uniform illumination due to highlight or object projection, and messy backgrounds. To locate the target text region, a focus line is assumed to pass through a text region. Next, connected component analysis and stroke width estimation based on location information of the focus line is used to locate the bounding box of the text region, and each box of connected components. A series of classifications are applied to identify whether each CC(Connected component) is text or non-text. Also, a modified K-means clustering method based on an HCL color space is applied to reduce the color dimension. A text binarization procedure based on location of text component and seed color pixel is then used to generate the final result.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.679-680
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• 2006

이 논문에서는 가장 많이 알려진 tracking 알고리즘인 Particle-Filter 의 단점을 motion vector 를 기반으로 예측한 sampling 방법과 K-means clustering 을 이용하여 해결하려고 한다. Tracking 에서의 문제는 다중의 유사한 객체들이 merge 후 split 될 때 제대로 추적을 하지 못하고 한 객체만을 추적 한다는 데에 있었다. 그리고 split 되어 객체별로 추적이 가능하더라도 이전에 추적한 객체를 올바로 labeling 하지 못하는 문제가 있다는 것이다. 이 merge-split 문제는 개량된 K-means clustering 을 이용하고, labeling 문제는 motion vector 를 이용한 개량된 sampling 방법으로 개선하였다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.1902-1910
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• 2009

This paper presents a graphical windows-based program for the education and training for novel network reduction. The object of developed simulator is to provide users with a simple and useable tool for gaining an intuitive feel for power system analysis. The developed simulator consists of the main module (MMI,GUI), the location marginal price module (LMP), the clustering module and network reduction module. Each module has a separate graphical and interactive interfacing window. The developed simulator needs with the PSS/E input data format, generator cost function, location information. Line admittances of reduced network was determined by using the power flow method(Newton-Raphson). So line flow of reduced network is almost same to original power system. Results of reduced network are compared on the window in the tabular format. Therefore, the developed simulator can be utilized as a useful tool for effective education and training for power system analysis.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.180-185
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• 2015

Digital infrared thermal imaging is a non-invasive adjunctive diagnostic technique that allows an examiner to visualize and quantify changes in skin surface temperature. The asymmetry of temperature differences between the diseased and the contralateral healthy body parts can be automatically analyzed and has been studied in many areas of medical science. In this paper, we propose a method for intelligent automatic asymmetry detection based on a K-means analysis and a YCbCr color model. The implemented software successfully visualizes an asymmetric distribution of colors with respect to the patients’ health status.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.128-133
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• 1998

In this paper, we present a parallel framework for tracking moving objects. Parallel framework consists largely of two parts:Search Space Reduction(SSR) and Tracking(TR). SSR is further composed of fuzzy clustering and prediction based on Kalman filter. TR is done by boundarymatching using the Hausdorff distance based on distance transform.