• Journal of Information Processing Systems
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• 제9권4호
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• pp.575-591
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• 2013

Most of the edge detection methods available in literature are gradient based, which further apply thresholding, to find the final edge map in an image. In this paper, we propose a novel method that is based on fuzzy logic for edge detection in gray images without using the gradient and thresholding. Fuzzy logic is a mathematical logic that attempts to solve problems by assigning values to an imprecise spectrum of data in order to arrive at the most accurate conclusion possible. Here, the fuzzy logic is used to conclude whether a pixel is an edge pixel or not. The proposed technique begins by fuzzifying the gray values of a pixel into two fuzzy variables, namely the black and the white. Fuzzy rules are defined to find the edge pixels in the fuzzified image. The resultant edge map may contain some extraneous edges, which are further removed from the edge map by separately examining the intermediate intensity range pixels. Finally, the edge map is improved by finding some left out edge pixels by defining a new membership function for the pixels that have their entire 8-neighbourhood pixels classified as white. We have compared our proposed method with some of the existing standard edge detector operators that are available in the literature on image processing. The quantitative analysis of the proposed method is given in terms of entropy value.

• 한국정보처리학회논문지
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• 제6권12호
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• pp.3703-3709
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• 1999

본 논문에서는 영상의 밝기 정보로부터 물체의 표면 형상을 재구성하는 새로운 접근 방법을 제시한다. 표면 재구성 문제를 최적화 문제로 정의하고 국지 해(local minima)에 빠지기 쉬운 기존의 경사법(gradient method) 대신 유전자 알고리즘(genetic algorithm)을 사용한다. 이를 위해 2차원 이미지에 적절한 유전자 표현 및 유전자 연산을 제시한다. 또한 입력 이미지를 단계별로 축소하고, 축소된 이미지에 유전자 알고리즘을 적용하여 큰 형상을 먼저 결정한 후 미세한 형상을 찾아내는 계층적 방법을 적용함으로써 유전자 알고리즘의 수렴 속도를 개선한다. 반사 모델로 기존의 람버션 반사 모델(Lambertian illumination model)에 거리 요소를 포함시켜 보다 현실과 비슷한 제약 조건을 주었으며 실험을 통해 제시된 방법의 타당성을 보인다.

• 한국해양공학회지
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• 제28권2호
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• pp.93-101
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• 2014

In general, particle simulation methods such as the MPS(Moving Particle Simulation) or SPH(Smoothed Particle Hydrodynamics) methods have some serious drawbacks for pressure solutions. The pressure field shows spurious high fluctuations both temporally and spatially. It is well known that pressure fluctuation primarily occurs because of the numerical approximation of the partial differential operators. The MPS and SPH methods employ a pre-defined kernel function in the approximation of the gradient and Laplacian operators. Because this kernel function is constructed artificially, an accurate solution cannot be guaranteed, especially when the distribution of particles is irregular. In this paper, we propose a particle simulation method based on the moving least-square technique for solving the partial differential operators using a Taylor-series expansion. The developed method was applied to the hydro-static pressure and dam-broken problems to validate it.

• 한국멀티미디어학회논문지
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• 제13권3호
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• pp.378-391
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• 2010

본 논문에서는 손가락 면의 영상으로 개인 식별이 가능한지를 실험하고 그 결과를 제시하였다. 이를 위하여 구배치(gradient)를 산출할 수 있는 오퍼레이터인 FFG 마스크(Facet Function Gradient mask)를 사용하고, F-알고리즘이라 명명한 새로운 방법으로 매칭 처리를 하였다. 이 알고리즘에서 손가락 면의 영상을 일정한 크기의 부영역(subregion)으로 나누고, 부영역은 다시 일정한 크기의 패치(patch)들로 나눈다. 각 패치에 같은 크기의 FFG 마스크들을 컨벌루션시키고, 마스크 별로 하나의 수치를 얻는다. 이들 수치를 특징매트릭스(feature matrix)로 삼고, norm에 의하여 동일인 여부를 판정한다. 두 개의 손 영상이 동일인의 것인 경우와 그렇지 않은 경우에 FFG 컨벌루션 수치 차 제곱 총화의 분포를 관찰한 결과 뚜렷한 차별성을 보였다. 이것은 손가락 면 영상의 식별 능력을 입증하는 결과이다. 100명의 손 영상을 5벌씩 촬영한 500장의 영상을 F-알고리즘에 의하여 실험한 결과 95.0%의 개인 식별률을 얻었다. 이러한 식별 능력과 식별률에 비추어 손가락 면(finger face)은 다른 biometric들과 대등한 수준으로 개인 식별을 위한 biometrics의 하나로 손색이 없음을 말할 수 있다

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1994년도 춘계학술대회
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• pp.23-26
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• 1994

A new algorithm using a measure for edge detection from ultrasonic image is proposed. Ultrasonic image is blurred by pre-processing for removing speckle noises and precise edge placement is not clear. Because extracted edge from blurred image is thick, a measure utilizing the absolute difference of mean between two windows is used to thin the thickness of extracted edge in blurred image. The algorithm is effective to process blurred image due to the noise filtering that remove speckle noises. Results of the proposed algorithm using a measure show good edge detection performance comparing with other gradient edge operators.

• 한국자동차공학회논문집
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• 제11권1호
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• pp.193-200
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• 2003

This paper proposes a novel algorithm to recognize the curve of a structured road. The proposed algorithm uses an LCF (Lane Curve Function) obtained by the transformation of a parabolic function defined on world coordinate into image coordinate. Unlike other existing methods, the algorithm needs no transformation between world coordinate and image coordinate owing to the LCF. In order to search for an LCF describing the lane best, the differential comparison between the slope of an assumed LCF and the phase angle of edge pixels in the LROI (Lane Region Of Interest) constructed by the LCF is implemented. As finding the true LCF, the lane curve is determined. The proposed method is proved to be efficient through various kinds of images, providing the reliable curve direction and the valid curvature compared to the real road.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권4호
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• pp.2109-2123
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• 2017

This paper presents a super-resolution reconstruction method based on sparse representation for two-dimensional bar code images. Considering the features of two-dimensional bar code images, Kirsch and LBP (local binary pattern) operators are used to extract the edge gradient and texture features. Feature extraction is constituted based on these two features and additional two second-order derivatives. By joint dictionary learning of the low-resolution and high-resolution image patch pairs, the sparse representation of corresponding patches is the same. In addition, the global constraint is exerted on the initial estimation of high-resolution image which makes the reconstructed result closer to the real one. The experimental results demonstrate the effectiveness of the proposed algorithm for two-dimensional bar code images by comparing with other reconstruction algorithms.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2011년 춘계학술대회논문집
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• pp.278-285
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• 2011

In the present study, the numerical prediction of the oil amount leaked from the hole of a damaged tank is investigated using the improved MPS (Moving Particle Semi-implicit) method, which was originally proposed by Koshizuka and Oka (1996) for incompressible flow. The governing equations, which consist of the continuity and Navier-Stokes equations, are solved by Lagrangian moving particles, and all terms expressed by differential operators should be replaced by the particle interaction models based on a Kernel function. The simulation results are validated though the comparison with the analytic solution based on Torricelli's equilibrium relation. Furthermore, a series of numerical simulations under the various conditions are performed in order to estimate more accurately the initial amount of leaked oil.

• 전자공학회논문지T
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• 제35T권1호
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• pp.1-6
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• 1998

본 연구는 부분방전 시스템을 이용하여 열화진단을 실시하였다. 열화 분석 방법으로는 위상각 부분방전 펄스진폭 열화시간과 위상각 부분방전 펄스수 열화시간의 양상을 왜도와 첨쇄도로 3차원 분석하여 열화의 정보로 이용하였다. 두번째로는 C (경도), G (무게중심)의 통계적 파라메터를 이용하여 방전의 군소화가 발생하는 시간을 구하여 그 지점으로부터 수명 4예측을 하였다.

• 대한수학회보
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• 제59권5호
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• pp.1255-1268
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• 2022

We consider the Schrödinger type operator 𝓛 = (-𝚫_ℍⁿ)² + V² on the Heisenberg group ℍⁿ, where 𝚫_ℍⁿ is the sub-Laplacian and the non-negative potential V belongs to the reverse Hölder class RH_s for s ≥ Q/2 and Q ≥ 6. We shall establish the (L^p, L^q) estimates for the Riesz transforms T_𝛼,𝛽,j = V^2𝛼𝛁^j_ℍⁿ𝓛^-𝛽, j = 0, 1, 2, 3, where 𝛁_ℍⁿ is the gradient operator on ℍⁿ, 0 < α ≤ 1-j/4, j/4 < 𝛽 ≤ 1, and 𝛽 - 𝛼 ≥ j/4.