• Ocean Systems Engineering
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• 제2권2호
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• pp.137-145
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• 2012

Recent developments in underwater image recognition methods have received large attention by the ocean engineering researchers. In this paper, an improved bi-dimensional empirical mode decomposition (BEMD) approach is employed to decompose the given underwater image into intrinsic mode functions (IMFs) and residual. We developed a joint algorithm based on BEMD and Canny operator to extract multi-pixel edge features at multiple scales in IMFs sub-images. So the multiple pixel edge extraction is an advantage of our approach; the other contribution of this method is the realization of the bi-dimensional sifting process, which is realized utilizing regional-based operators to detect local extreme points and constructing radial basis function for curve surface interpolation. The performance of the multi-pixel edge extraction algorithm for processing underwater image is demonstrated in the contrast experiment with both the proposed method and the phase congruency edge detection.

• Journal of electromagnetic engineering and science
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• 제1권1호
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• pp.78-82
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• 2001

For fast capacitance computation, a simple mesh refinement technique on MLFMA(Multi-Level Fast Multipole Algorithm) is proposed The triangular meshes are refined mainly in the area which has heavy charge density. The technique is applied to the capacitance extraction of three dimensional conductors. The results show good convergence with comparable accuracy. An adaptive technique concerned with MLFMA is useful to reduce computation time and the number of elements without additional computational efforts in large three dimensional problems.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2007년도 하계종합학술대회 논문집
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• pp.405-406
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• 2007

In this paper, we propose feature extraction and tracking algorithm using multi resolution in 2-dimensional wavelet domain. Feature extraction selects feature points using 2-level wavelet transform in interested region. Feature tracking estimates displacement between current frame and next frame based on feature point which is selected feature extraction algorithm. Experimental results show that the proposed algorithm confirmed a better performance than the existing other algorithms.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2005년도 추계학술대회 및 정기총회
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• pp.103-111
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• 2005

In this paper, we have designed a deployment process system that extract and integrate information related to technology and market opportunities through searching for external environment and internal condition on multi-dimensional space in order to generate new research themes. It is expected that this theme extraction model could be contributed to the maximization of R&D productivity by systemization of the opportunity extraction process for generating research themes in R&D center or laboratory.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.359-362
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• 2004

In multi-dimensional image, ICA-based feature extraction algorithm, which is proposed in this paper, is for the purpose of detecting target feature about pixel assumed as a linear mixed spectrum sphere, which is consisted of each different type of material object (target feature and background feature) in spectrum sphere of reflectance of each pixel. Landsat ETM+ satellite image is consisted of multi-dimensional data structure and, there is target feature, which is purposed to extract and various background image is mixed. In this paper, in order to eliminate background features (tidal flat, seawater and etc) around target feature (laver farm) effectively, pixel spectrum sphere of target feature is projected onto the orthogonal spectrum sphere of background feature. The rest amount of spectrum sphere of target feature in the pixel can be presumed to remove spectrum sphere of background feature. In order to make sure the excellence of feature extraction method based on ICA, which is proposed in this paper, laver farm feature extraction from Landsat ETM+ satellite image is applied. Also, In the side of feature extraction accuracy and the noise level, which is still remaining not to remove after feature extraction, we have conducted a comparing test with traditionally most popular method, maximum-likelihood. As a consequence, the proposed method from this paper can effectively eliminate background features around mixed spectrum sphere to extract target feature. So, we found that it had excellent detection efficiency.

• 대한전자공학회논문지SD
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• 제39권3호
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• pp.73-84
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• 2002

불규칙하고 복잡한 다층(multi-layer) VLSI 배선의 커패시턴스 추출을 위한 빠르고 정확한 새로운 방법을 개발하였다. 복잡한 다층 배선구조에서 3차원 field-solver를 사용하여 커패시턴스를 구하는 것은 현실적이지 않기 때문에 근사적 3차원 커패시턴스 추출 방법을 제안한다. 꺽이는 부분(bend)과 상이한 배선사이의 거리를 갖는 동일한 층내의 배선은 불연속한 부분과 만나는 곳을 분할하고 각각의 부분에 2차원 커패시턴스 추출 방법을 사용하여 커패시턴스를 추출하였다. 또한 차폐층(shielding layer)을 갖는 다층 배선 구조에서의 커패시턴스는 시스템 내의 전하의 분포를 조사함으로써 시스템을 간소화 시킨 후 평판 그라운드 기반 2차원 커패시턴스와 간단한 구조로부터 독립적으로 계산될 수 있는 차폐효과를 결합하여 근사적3차원 커패시턴스 추출 방법을 적용하였다. 불규칙한 다층 배선 구조에 대하여 설계된 레이아웃으로부터 해석적으로 구할 수 있는 변수와 평판 그라운드를 사용한 2차원 커패시턴스 추출 방법을 사용하므로 정확하면서도 신속하게 커패시턴스를 추출할 수 있어 일반적인 3차원 방법보다 비용 측면에서 훨씬 효과적이다. 제안된 근사적 3차원 방법을 통해 구한 커패시턴스는 3차원 field-solver를 기반으로 구한 커패시턴스와 오차율 5% 이내의 정확성을 나타낸다.

• 한국전자파학회:학술대회논문집
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• 한국전자파학회 2001년도 종합학술발표회 논문집 Vol.11 No.1
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• pp.140-144
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• 2001

This paper describes to extend the MLFMA(Multi-Level Fast Multipole Algorithm) for three-dimensional capacitance computation in the case of conductors embedded in an arbitrary dielectric medium. The triangular meshes are used and refined in the area which has heavy charge density. This technique is applied to the capacitance extraction of three-dimensional structures with multiple dielectrics. The results show good convergence with the comparable accuracy, and this adaptive technique coupled with MLFMA is useful to reduce computing time and the number of elements without additional computational efforts in large three dimensional problems.

• 한국전자파학회논문지
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• 제13권1호
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• pp.80-86
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• 2002

본 논문에서는 유전체층을 가진 3차원 도체의 정전용량 계산을 위한 적응요소 MLFMA을 제안하였다. 고속화 알고리즘인 MLFMA와 더불어 높은 전하밀도를 가지는 영역에서 삼자요소를 세분화함으로써 효율적으로 요소를 분할하게 된다. 제안된 기법은 유전체 층위의 3차원 도체의 정전용량을 계산하는데 적용되어 균일한 요소에 의한 계산결과의 수렴보다 빠른 결과를 얻을 수 있었다. 또한, 3차원의 복잡한 구조를 가진 문제의 해석에 있어서도 과도한 추가계산시간을 요구하지 않으므로, 제안된 방법을 MLFMA의 장점에 부합되는 적절한 기법이라 할 수 있다.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1998년도 제27회 춘계학술대회
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• pp.314-320
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• 1998

Wear debris morphology is closely related to the wear mode and mechanism occured. Image recognition of wear debris is, therefore, a powerful tool in wear monitoring. But it has usually required expert's experience and the results could be too subjective. Development of automatic tools for wear debris recognition is needed to solve this problem. In this work, an algorithm for automatic wear debris recognition was suggested and implemented by PC base software. The presented method defined a characteristic 3-dimensional feature space where typical types of wear debris were separately located by the knowledge-based system and compared the similarity of object wear debris concerned. The 3-dimensional feature space was obtained from multiple feature vectors by using a multi-dimensional scaling technique. The results showed that the presented automatic wear debris recognition was satisfactory in many cases application.

• Tribology and Lubricants
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• 제15권2호
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• pp.206-211
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• 1999

Wear debris morphology is closely related to the wear mode and mechanism occured. Image recognition of wear debris is, therefore, a powerful tool in wear monitoring. But it has usually required expert's experience and the results could be too subjective. Development of automatic tools for wear debris recognition is needed to solve this problem. In this work, an algorithm for automatic wear debris recognition was suggested and implemented by PC base software. The presented method defined a characteristic 3-dimensional feature space where typical types of wear debris were separately located by the knowledge-based system and compared the similarity of object wear debris concerned. The 3-dimensional feature space was obtained from multiple feature vectors by using a multi-dimensional scaling technique. The results showed that the presented automatic wear debris recognition was satisfactory in many cases application.