• 한국컴퓨터정보학회논문지
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• 제21권4호
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• pp.9-15
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• 2016

Symmetry is everywhere in the world around us from galaxy to microbes. From ancient times symmetry is considered to be a reflection of the harmony of universe. Symmetry is not only a significant clue for human cognitive process, but also useful information for computer vision such as image understanding system. Application areas include face detection and recognition, indexing of image database, image segmentation and detection, analysis of medical images, and so on. The technique used in this paper extracts edges, and the perpendicular bisector of any two edge points is considered to be a candidate axis of symmetry. The coefficients of candidate axis are accumulated in the coefficient space. Then the axis of symmetry is determined to be the line for which the coefficient histogram has maximum value. In this paper, an improved method is proposed that utilizes the directional information of edges, which is a byproduct of the edge detection process. Experiment on 20 test images shows that the proposed method performs 22.7 times faster than the original method. In another test on 5 images with 4% salt-and-pepper noise, the proposed method detects the symmetry successfully, while the original method fails. This result reveals that the proposed method enhances the speed and accuracy of detection process at the same time.

• 대한수학회지
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• 제56권4호
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• pp.917-934
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• 2019

In this paper, we give some classifications of almost Kenmotsu 3-manifolds under homogeneity and some symmetry conditions.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2002년도 춘계학술대회
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• pp.51-73
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• 2002

Empirical likelihood ratio method is a new technique in nonparametric inference developed by A. Owen (1988, 2001). Sometimes empirical likelihood has difficulties to define itself. As such a case in point, we discuss the way to define a modified empirical likelihood for the location of symmetry using well-known points of symmetry as a side conditions. The side condition of symmetry is defined through a finite subset of the infinite set of constraints. The modified empirical likelihood under symmetry studied in this paper is to construct a constrained parameter space $\theta+$ of distributions imposing known symmetry as side information. We show that the usual asymptotic theory (Wilks theorem) still hold for the empirical likelihood ratio on the constrained parameter space and the asymptotic distribution of the empirical NPMLE of difference of two symmetric points is obtained.

• Journal of the Korean Data and Information Science Society
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• 제16권2호
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• pp.227-236
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• 2005

A chi-squared test of spherical symmetry is suggested. This test is easy to apply in practice since it is easy to compute and has a limiting chi-squared distribution under spherical symmetry. The result of Park(1998) can be used to show that it has the limiting chi-squared distribution. A simulation study is conducted to study the accuracy, in finite samples, of the limiting distribution. Finally, a simulation study that compares the power of our test with those of other tests of spherical symmetry is performed.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2005년도 춘계학술대회
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• pp.182-184
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• 2005

In this study, we propose a chi-squared test of spherical symmetry. The advantage of this test is that the test statistic and its asymptotic p-value are easy to compute. A simulation study is conducted to study the accuracy, in finite samples, of the limiting distribution of the test statistic under spherical symmetry. The power of our test is compared with those of other tests for spherical symmetry in various alternative distributions via simulation.

• 인터넷정보학회논문지
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• 제5권1호
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• pp.59-66
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• 2004

대칭 영역 탐색은 대칭 정보를 이용하여 사전 정보 없이 얼굴영역을 추출 할 수 있다. 그러나 눈, 코, 입 등과 같은 얼굴의 특징 부위보다 탐색할 마스크의 크기가 커져야 함으로 이 방법은 계산 시간이 많이 걸린다. 본 논문에서는 얼굴 영상에 대하여 사전 정보 없이, 적은 계산량으로 얼굴 영역 추출이 가능하도록 대칭 영역 탐색 및 웨이블릿 변환을 이용하여 얼굴 영역의 추출과 그 특징에서의 대칭간에 따른 영상을 이용하여 원영상에서는 영역 분할을 통한 얼굴 영역 추출 방법을 제안하고 실험을 통하여 이를 확인하였다.

• Journal of the Korean Statistical Society
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• 제21권2호
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• pp.179-185
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• 1992

A model is proposed for describing agreement between two raters on a nominal categorical scale. This model has a structure of symmetry plus main-diagonal equiprobability, which is a special case of the quasi-symmetry model. An example is given.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
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• pp.223-226
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• 2000

In this paper, we report detects system algorithm, adapted a perimetric mask and a generalized symmetry system, to detect a transformable material and find out a minute error cannot be noticed by a naked eye. In this thesis, supposed a stable detecting system applied a general image processing theory and perimetric mash algorithm to detect badness. And finally, detected some vague errors with the application of symmetry transform algorithm that accumulate a symmetry of minute error and put stress on it.

• Journal of the Korean Statistical Society
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• 제21권1호
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• pp.59-69
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• 1992

A measure is proposed to represent the degree of residuals from the symmetry model for square contingency tables with nominal categories. The measure is derivedby modifying the sum of squared singular values for a skew symmetric matrix of the residuals from the symmetry model. The proposed measure would be useful for comparing the degree of residuals from the symmetry model in several tables.

• 한국컴퓨터정보학회논문지
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• 제20권9호
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• pp.31-37
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• 2015

Symmetry is easily found in animals and plants as well as in artificial structures. It is useful not only for human cognitive process but also for image understanding by computer. Application areas include face detection and recognition, indexing of image database, image segmentation and detection, and analysis of medical images. The method used in this paper extracts edges, and the perpendicular bisector of any pair of selected edge points is considered to be a candidate axis of symmetry. The coefficients of the perpendicular bisectors are accumulated in the coefficient space. Axis of symmetry is determined to be the line for which the histogram has maximum value. This method shows good results, but the usefulness of the method is restricted because the amount of computation increases proportional to the square of the number of edges. In this paper, an acceleration method is proposed which performs $2^{2n}$ times faster than the original one. Experiment on 20 test images shows that the proposed method using level-3 image segmentation performs 63.9 times faster than the original method.