• Ocean Systems Engineering
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• v.2 no.2
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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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• v.1 no.1
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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.

• Proceedings of the IEEK Conference
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• 2007.07a
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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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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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.

• Proceedings of the KSRS Conference
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• 2004.10a
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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.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.3
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• pp.73-84
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• 2002

Fast and accurate new capacitance determination methodology for non-uniform complicated multi-layer VLSI interconnects is presented. Since a capacitance determination of intricate multi-layer interconnects using 3-dimensional field-solver is not practical, quasi-3-dimensional methodology is presented. Interconnects with discontinuity (i.e., bend structure and different spacing between lines, etc.) are partitioned. Then, each partial capacitance of divided parts is extracted by using 2-dimensional extraction methodology. For a multi-layer interconnects with shielding layer, the system can be simplified by investigating a distribution of charge in it. Thereby, quasi-3-dimensional capacitance for multi-layer interconnects can be determined by combining solid-ground based 2-dimensional capacitance and shielding effect which is independently determined with layout dimensions. This methodology for complicated multi-layer interconnects is more accurate and cost-efficient than conventional 3-dimensional methodology It is shown that the quasi-3-dimensional capacitance methodology has excellent agreement with 3-dimensional field- solver-based results within 5% error.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2001.11a
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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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.1
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• pp.80-86
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• 2002

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 with least additional computational efforts in large three dimensional problems.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.04a
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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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• v.15 no.2
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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.