• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.179-187
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• 2010

Miniature spectrometers can be applied for various purposes in wide areas. This paper shows how a wellmade spectrometer on-a-chip of a low performance and low-cost filter-array can be used for recognizing types of red wine. Light spectra are processed through a filter-array of a spectrometer after they have passed through the wine in the cuvettes. Without recovering the original target spectrum, pattern recognition methods are introduced to detect the types of wine. A wavelength cross-correlation turns out to be a good distance metric among spectra because it captures their simultaneous movements and it is affine invariant. Consequently, a well-designed spectrometer is reliability in terms of its repeatability.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.795-800
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• 2008

카메라로 입력되는 영상에서 객체를 인식하기 위한 노력은, 기존의 컴퓨터 비전분야에서 좋은 이슈로 연구되고 있다. 영상 내부에 등장하는 객체를 인식하고 해당 객체를 포함하고 있는 전체 이미지에서 현재 영상의 위치를 인식하기 위해서는, 영상 내에 등장할 객체에 대한 트레이닝이 필요하다. 본 논문에서는 영상에 등장할 객체에 대해서, 특징 점을 검출(feature detection)하고 각 점들이 가지는 픽셀 그라디언트 방향의 벡터 값들을 그 이웃하는 벡터 값들과 함께 DoG(difference-of-Gaussian)함수를 이용하여 정형화 한다. 이는 추후에 입력되는 영상에서 검출되는 특징 점들과 그 이웃들 간의 거리나 스케일의 비율 등의 파리미터를 이용하여 비교함으로써, 현재 특징 점들의 위치를 추정하는 정보로 사용된다. 본 논문에서는 광역의 시설 단지를 촬영한 인공위성 영상을 활용하여 시설물 내부에 존재는 건물들에 대한 초기 특징 점들을 검출하고 데이터베이스로 저장한다. 트레이닝이 마친 후에는, 프린트된 인공위성 영상내부의 특정 건물을 카메라를 이용하여 촬영하고, 이 때 입력된 영상의 특징 점을 해석하여 기존에 구축된 데이터베이스 내의 특징 점과 비교하는 과정을 거친다. 매칭되는 특징 점들은 DoG로 정형화된 벡터 값들을 이용하여 해당 건물에 대한 위치를 추정하고, 3차원으로 기 모델링 된 건물을 증강현실 기법을 이용하여 영상에 정합한 후 가시화 한다.

• Journal of applied mathematics & informatics
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• v.8 no.2
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• pp.345-360
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• 2001

Affine invariant sufficient conditions are given for two local convergence theorems involving inexact Newton-like methods. The first uses conditions on the first Frechet-derivative whereas the second theorem employs hypotheses on the mth(m≥2 an integer). Radius of convergence as well as rate of convergence results are derived. Results involving superlinear convergence and known to be true for inexact Newton methods are extended here. Moreover, we show that under hypotheses on the mth Frechet-derivative our radius of convergence can sometimes be larger than the corresponding one in [10]. This allows a wider choice for the initial guess. A numerical example is also provided to show that our radius of convergence is larger than the one in [10].

• Journal for History of Mathematics
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• v.28 no.4
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• pp.181-190
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• 2015

In spite of various attempts to characterize the ontological status of space-time, Newtonian substantivalism and Leibnizian relationism, what is really at issue in the controversy between the two parties is by no means clear. This essay argues that from the perspective of space-time symmetries, classical space-time can be unambiguously classified as substantival space-time and relational space-time. The symmetries of space-time theories distinguish the invariant geometric relationships between events. The essential difference between the two space-times stems from whether or not there exists the affine structure that distinguishes the inertial trajectories of a given body.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.544-546
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• 2000

이 논문에서는 CAGD 및 기하모델링 분야에서 최근 발표된 Universal Parametrization의 계산적 또는 응용적 특성을 고찰하고자 한다. Universal Parametrization을 이용하여 구한 B-spline의 곡선이나 곡면에 아주 자연스러운 특성을 가지고 있다. 뿐만 아니라, 다른 매개변수(Parametrization)을 이용하는 경우, 점들의 기하학적 분포나 곡선/곡면의 차수에 따라 결과의 차이가 심한 경우가 있으나 새로운 방법은 B-spline이라는 기초함수의 특성을 고려한 매개변수법이므로 이러한 결과의 차이를 최대한 줄이는 특성이 있다. 또한 점 데이터에 관해서 Affine Invariant하고 Semi-localness의 특성을 보인다. 이외에도, 계산적인 관점에서 강인성을 보유하고 있고, 많은 응용분야에서 쉽게 자유곡선이나 자유곡면 모델링을 할 수 있도록 한다. 한 예로, 3D 다각형 메쉬로부터 B-spline을 이용한 자유곡면 모델을 구하는 소프트웨어 툴을 설명한다.

• The Pure and Applied Mathematics
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• v.17 no.1
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• pp.1-27
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• 2010

Wu and Zhao [17] provided a semilocal convergence analysis for a Newton-type method on a Banach space setting following the ideas of Frontini and Sormani [9]-[11]. In this study first: we point out inconsistencies between the hypotheses of Theorem 1 and the two examples given in [17], and then, we provide the proof in affine invariant form for this result. Then, we also establish new convergence results with the following advantages over the ones in [17]: weaker hypotheses, and finer error estimates on the distances involved. A numerical example is also provided to show that our results apply in cases other fail [17].

• Korean Journal of Remote Sensing
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• v.24 no.3
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• pp.235-243
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• 2008

Object tracking is a common vision task to detect and trace objects between consecutive frames. It is also important for a variety of applications such as surveillance, video based traffic monitoring system, and so on. An efficient moving vehicle clustering and tracking algorithm suitable for traffic monitoring system is proposed in this paper. First, automatic background extraction method is used to get a reliable background as a reference. The moving blob(object) is then separated from the background by mean shift method. Second, the scale invariant feature based method extracts the salient features from the clustered foreground blob. It is robust to change the illumination, scale, and affine shape. The simulation results on various road situations demonstrate good performance achieved by proposed method.

• Bulletin of the Korean Mathematical Society
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• v.24 no.1
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• pp.31-37
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• 1987

I want to focus on developments in the areas of general relativity and gauge theory. The topics to be considered are the singularity theorms of Hawking and Penrose, the positivity of mass, instantons on the four-dimensional sphere, and the string picture of quantum gravity. I should mention that I will not have time do discuss either classical mechanics or symplectic structures. This is especially unfortunate, because one of the roots of differential geometry is planted firmly in mechanics, Cf. [GS]. The French geometer Elie Cartan first formulated his invariant approach to geometry in a series of papers on affine connections and general relativity, Cf. [C]. Cartan was trying to recast the Newtonian theory of gravity in the same framework as Einstein's theory. From the historical perspective it is significant that Cartan found relativity a convenient framework for his ideas. As about the same time Hermann Weyl in troduced the idea of gauge theory into geometry for purposes much different than those for which it would ultimately prove successful, Cf. [W]. Weyl wanted to unify gravity with electromagnetism and though that a conformal structure would fulfill thel task but Einstein rebutted this approach.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.343-352
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• 2000

In this study. the author proposes a nonhierarchical clustering method. called the "Double K-Means Clustering", which performs clustering of multivariate observations with the following algorithm: Step I: Carry out the ordinary K-means clmitering and obtain k temporary clusters with sizes $n_1$,... , $n_k$, centroids $c_$1,..., $c_k$ and pooled covariance matrix S. $\bullet$ Step II-I: Allocate the observation x, to the cluster F if it satisfies ..... where N is the total number of observations, for -i = 1, . ,N. $\bullet$ Step II-2: Update cluster sizes $n_1$,... , $n_k$, centroids $c_$1,..., $c_k$ and pooled covariance matrix S. $\bullet$ Step II-3: Repeat Steps II-I and II-2 until the change becomes negligible. The double K-means clustering is nearly "optimal" under the mixture of k multivariate normal distributions with the common covariance matrix. Also, it is nearly affine invariant, with the data-analytic implication that variable standardizations are not that required. The method is numerically demonstrated on Fisher's iris data.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.66-77
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• 2011

We propose a framework for grouping photographic advertising images that employs a hierarchical indexing scheme based on efficient feature combinations. The study provides one specific application of effective tools for monitoring photographic advertising information through online and offline channels. Specifically, it develops a preprocessor for advertising image information tracking. We consider both global features that contain general information on the overall image and local features that are based on local image characteristics. The developed local features are invariant under image rotation and scale, the addition of noise, and change in illumination. Thus, they successfully achieve reliable matching between different views of a scene across affine transformations and exhibit high accuracy in the search for matched pairs of identical images. The method works with global features in advance to organize coarse clusters that consist of several image groups among the image data and then executes fine matching with local features within each cluster to construct elaborate clusters that are separated by identical image groups. In order to decrease the computational time, we apply a conventional clustering method to group images together that are similar in their global characteristics in order to overcome the drawback of excessive time for fine matching time by using local features between identical images.