• 한국멀티미디어학회논문지
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• 제5권2호
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• pp.158-166
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• 2002

본 논문에서는 윤곽선 세그먼트의 양 끝점을 잇는 직선과 곡선의 길이의 비율로 윤곽선 변동율을 정의하고, 이로부터 윤곽선의 형태를 기술하는 방법을 제안하였다. 윤곽선 변동율은 윤곽선 세그먼트로부터 계산되기 때문에 회전이나 크기 변형에 불변하는 윤곽선 세그먼트를 추출해야 한다. 이를 위하여 전체 윤곽선의 길이에 비례하는 상대적인 길이로 윤곽선을 분할하고 윤곽선 상의 모든 점을 분할점으로 하는 중첩된 윤곽선 세그먼트를 이용하였다. 윤곽선 변동율은 윤곽선 세그먼트의 단위 길이에 따라 국소적 또는 전역적인 특징을 나타내므로, 윤곽선 변동율의 분포를 나타내는 특징 벡터로 물체의 형태를 기술하고, 단위 길이별로 특징 벡터를 비교하여 윤곽선 형태의 유사도를 계산한다. 제안된 방법을 구현하여 15종의 물고기 영상에 대하여 회전 및 크기 변형을 가한 총 165개의 영상에 대하여 실험한 결과, 회전 및 크기 변형에 대한 불변성은 물론 정규화된 체인코드 히스토그램(NCCH)과 링 프로젝션(TRP)을 이용한 방법에 비하여 군집화 능력이 우수함을 확인할 수 있었다.

• 한국통신학회논문지
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• 제28권11C호
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• pp.1140-1151
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• 2003

본 논문에서는 변형 Otsu 이진화 방법과 Hu 모멘트를 기반으로 밝기, 명암도, 크기, 회전, 위치 변화에 강인한 얼굴 인식 방법을 제안한다. 제안하는 변형 Otsu 이진화 방법은 기존의 Otsu 이진화 방법으로부터 또 다른 문턱치 값을 결정하고 이로부터 얻어진 이진 얼굴 영상 2개를 사용함으로써 이진 영상 하나보다 고차원의 특징벡터를 추출할 수 있고, 기존의 Otsu 이진화 방법과 마찬가지로 밝기 및 명암도 변화에 강인한 속성을 가지고 있다. 특징 값으로는 Hu 모멘트를 사용함으로써 크기, 회전, 위치 변화에 강인한 특성을 추가로 가지고 있다 기존의 주요 성분 분석(Principal Component Analysis, PCA) 방법과 제안한 방법을 비교 실험한 결과, 위에서 언급한 5가지 다양한 환경 변화에 대하여 PCA 방법의 평균 인식률은 olivetti Research Laboratory (ORL) 데이터베이스와 AR 데이터베이스에 대해서 각각 68.4%와 51.2%이고, 제안한 방법의 평균 인식률은 각각 93.2%와 81.4%로서 제안한 방법의 인식 성능이 우수함을 확인하였다.

• 한국멀티미디어학회논문지
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• 제10권9호
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• pp.1125-1134
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• 2007

본 논문에서는 가보 웨이블릿(Gabor Wavelet)을 이용한 회전 변화에 무관한 질감 분류 기법을 제안한다. 기존의 방법들은 대용량 질감 데이터베이스에서 낮은 정정분류비(Correct Classification Rate)를 나타내었다. 제안한 방법은 가보 웨이블릿 필터링 된 영상에서 전역 특징 벡터(Global Feature Vector)와 지역 특징행렬(Local Feature Matrix)을 정의하였다. 회전 변화에 무관한 두 가지 특징 그룹을 이용하여 개선된 유사도 측정 판별식(Discriminant)을 정의하였으며, 실험을 통하여 대용량 질감 데이터베이스에 적용한 결과 향상된 정정분류비를 얻을 수 있었다. 또한 질감 영상 스펙트럼의 대칭성을 이용하여 기존의 방법보다 실험회수를 50% 가까이 감소시켰다 결론적으로 112개의 브로다츠(Brodatz) 질감 클래스에서 비교 방법에 따라 차이는 있으나 $2.3%{\sim}15.6%$의 향상된 정정분류비를 얻었다.

• Steel and Composite Structures
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• 제41권6호
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• pp.831-850
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• 2021

Surface subsidence caused by mining subsidence has an impact on neighboring structures and utilities. In other words, subsurface voids created by mining or tunneling activities induce soil movement, exposing buildings to physical and/or functional destruction. Soil-structure is evaluated employing probability distribution laws to account for their uncertainty and complexity to estimate structural vulnerability. In this study, to investigate the displacement field and surface settlement profile caused by mining subsidence, on the basis of a Winklersoil model, analytical equations for the moment-rotation response ofsoil during mining induced ground movements are developed. To define the full static moment-rotation response, an equation for the uplift-yield state is constructed and integrated with equations for the uplift- and yield-only conditions. The constructed model's findings reveal that the inverse of the factor of safety (x) has a considerable influence on the moment-rotation curve. The maximal moment-rotation response of the footing is defined by X = 0:6. Despite the use of Winkler model, the computed moment-rotation response results derived from the literature were analyzed through the ELM-SVM hybrid of Extreme Learning Machine (ELM) and Support Vector Machine (SVM). Also, Monte Carlo simulations are used to apply continuous random parameters to assess the transmission of ground motions to structures. Following the findings of RMSE and R2, the results show that the choice of probabilistic laws of input parameters has a substantial impact on the outcome of analysis performed.

• Bulletin of the Korean Chemical Society
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• 제31권10호
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• pp.2841-2848
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• 2010

Quasiclassical trajectory (QCT) method has been used to investigate stereodynamics information of the reaction $O(^1D)+H_2{\rightarrow}\;OH$+H on the DK (Dobbyn and Knowles) potential energy surface (PES) at a collision energy of 23.06 kcal/mol, with the initial quantum state of reactant $H_2$ being set for v = 0 (vibration quantum number) and j = 0-5 (rotation quantum number). The PDDCSs (polarization dependent differential cross sections) and the distributions of P($\theta_r$), P($\phi_r$), P($\theta_r$, $\phi_r$) have been presented in this work. The results demonstrate that the products are both forward and backward scattered. As j increases, the backward scattering becomes weaker while the forward scattering becomes slightly stronger. The distribution of P($\theta_r$) indicates that the product rotational angular momentum j' tends to align along the direction perpendicular to the reagent relative velocity vector k, but this kind of product alignment is found to be rather insensitive to j. Furthermore, the distribution of P($\phi_r$) indicates that the rotational angular momentum vector of the OH product is preferentially oriented along the positive direction of y-axis, and such product orientation becomes stronger with increasing j.

• Journal of Multimedia Information System
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• 제6권2호
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• pp.91-98
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• 2019

Many researchers have attempted to recognize three-dimensional faces using feature points extracted from two-dimensional facial photographs. However, due to the limit of flat photographs, it is very difficult to recognize faces rotated more than 15 degrees from original feature points extracted from the photographs. As such, it is difficult to create an algorithm to recognize faces in multiple angles. In this paper, it is proposed a new algorithm to recognize three-dimensional face recognition based on feature points extracted from a flat photograph. This method divides into six feature point vector zones on the face. Then, the vector value is compressed and expanded according to the rotation angle of the face to recognize the feature points of the face in a three-dimensional form. For this purpose, the average of the compressibility and the expansion rate of the face data of 100 persons by angle and face zone were obtained, and the face angle was estimated by calculating the distance between the middle of the forehead and the tail of the eye. As a result, very improved recognition performance was obtained at 30 degrees of rotated face angle.

• Journal of Computational Design and Engineering
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• 제3권4호
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• pp.337-348
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• 2016

An experimental approach is presented for the measurement of wear that is common in the threading of cold-forged steel. In this work, the first objective is to measure wear on various types of roll taps manufactured to tapping holes in microalloyed HR45 steel. Different geometries and levels of wear are tested and measured. Taking their geometry as the critical factor, the types of forming tap with the least wear and the best performance are identified. Abrasive wear was observed on the forming lobes. A higher number of lobes in the chamber zone and around the nominal diameter meant a more uniform load distribution and a more gradual forming process. A second objective is to identify the most accurate data-mining technique for the prediction of form-tap wear. Different data-mining techniques are tested to select the most accurate one: from standard versions such as Multilayer Perceptrons, Support Vector Machines and Regression Trees to the most recent ones such as Rotation Forest ensembles and Iterated Bagging ensembles. The best results were obtained with ensembles of Rotation Forest with unpruned Regression Trees as base regressors that reduced the RMS error of the best-tested baseline technique for the lower length output by 33%, and Additive Regression with unpruned M5P as base regressors that reduced the RMS errors of the linear fit for the upper and total lengths by 25% and 39%, respectively. However, the lower length was statistically more difficult to model in Additive Regression than in Rotation Forest. Rotation Forest with unpruned Regression Trees as base regressors therefore appeared to be the most suitable regressor for the modeling of this industrial problem.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1404-1407
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• 2002

Although we look at objects as 2D images through our eyes, we can reconstruct the shape and/or depth of objects. In order to realize this ability using computers, it is required that the method which can estimate the 3D features of object from 2D images. As feature which represents 3D shapes effectively, three dimensional vector autoregressive model is pro- posed. If this feature is associated other feature of 2D shape, then above aim might be achieved. On the other hand, as feature which represents 2D shapes, quasi moment features is proposed. As the first step of association of these features, we constructed real time simulator that computes both of two features concurrently from object data (3D curves) . This simulator can also rotate object and estimate the rotation The method using 3D VAR model estimates the rotation correctly, but the estimation by quasi moment features includes much errors. This reason would be that projected images are constructed by the points only, and doesn't have enough sizes to estimate the correct 3D rotation parameters.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
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• pp.313-320
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• 1999

In this paper, a translation, rotation and scale invariant system for the classification of closed 2D images using the bispectrum of a contour sequence and the weighted fuzzy mean method is derived and compared with the classification process using one of the competitive neural algorithm, called a LVQ(Learning Vector Quantization). The bispectrun based on third order cumulants is applied to the contour sequences of the images to extract fifteen feature vectors for each planar image. These bispectral feature vectors, which are invariant to shape translation, rotation and scale transformation, can be used to represent two-dimensional planar images and are fed into an classifier using weighted fuzzy mean method. The experimental processes with eight different shapes of aircraft images are presented to illustrate the high performance of the proposed classifier.

• 전자공학회논문지B
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• 제33B권3호
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• pp.79-87
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• 1996

A new method for recognizing and locating partially occluded or overlapped two-dimensional objects regardless of their size, translation, and rotation, is presented. Dominant points approximating occuluding contoures of objects are generated by finding local maxima of smoothed k-cosine function, and then used to guide the contour segment matching procedure. Primitives between the dominant points are produced by projecting the local contours onto the line between the dominant points. Robust classification of primitives. Which is crucial for reliable partial shape matching, is performed using adaptive resonance theory (ART2). The matched primitives having similar scale factors and rotation angles are detected in the hough space to identify the presence of the given model in the object scene. Finally the translation vector is estimated by minimizing the mean squred error of the matched contur segment pairs. This model-based matching algorithm may be used in diveerse factory automation applications since models can be added or changed simply by training ART2 adaptively without modifying the matching algorithm.