• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.6
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• pp.88-98
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• 1998

Subspace classifier is a popular pattern recognition method based on Karhunen-Loeve transform. This classifier describes a high dimensional pattern by using a reduced dimensional subspace. Because of the loss of information induced by dimensionality reduction, however, a subspace classifier sometimes shows unsatisfactory recognition performance to the patterns having quite similar principal components each other. In this paper, we propose the use of multiple novelty neural network classifiers constructed on novelty vectors to adopt minor components usually ignored and present a method of improving recognition performance through combining those with the subspace classifier. We develop the proposed classifier on handwritten numeral database and analyze its properties. Our proposed classifier shows better recognition performance compared with other classifiers, though it requires more weight links.

• Journal of Korea Multimedia Society
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• v.8 no.2
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• pp.174-180
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• 2005

Points of sharp variations in image are the most important components when we analyze the features of image. And they include a variety of information about image's shape and location etc. So a lot of researches for detecting edges have been continued. Edge detection operators which were used at the early stage of the research were to utilize relations among neighboring pixels. These methods detect edge at all boundaries, therefore they perform edge detection twice about curves below some width such as line-edge. In the meantime, wavelet transform which is presented as a new technique of signal processing field provides multiscale edge detection and is being applied widely in many fields that analyze edge-like characteristic. Therefore, in this paper we detected line-edge with new 2-D wavelet function which is independent of line's width.

• Journal of Sensor Science and Technology
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• v.24 no.3
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• pp.169-174
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• 2015

In this study, we developed a system to detect the various defects in the metallic objects using the phenomenon that the defects cause the changes of the natural resonant frequencies. Our system consists of a FFT Amp, an Auto Impact Hammer, a Hammer controller and a PC. Auto Impact Hammer creates vibrations in the metallic objects when tapped on the surface. These vibrational signals are converted to the voltage signals by an acceleration sensor attached to the metallic part surface. These analog voltage signals were fed into an ADC (analog-digital converter) and an FFT (fast fourier transform) conversion in the FFT Amp to obtain the digital data in the frequency domain. Labview graphical program was used to process the digital data from th FFT amp to display the spectrum. We compared those spectra with the standard spectrum to find the shifts in the resonant frequencies of the metal parts, and thus detecting the defects. We used PCB's acceleration sensor and TI's TMS320F28335 DSP (digital signal processor) to obtain the resolution of 2.93 Hz and to analyze the frequencies up to 44 kHz.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.324-329
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• 2005

In this paper, a robust $H\infty$ stabilization problem to a uncertain discrete-time nonlinear systems with time-delay via fuzzy static output feedback is investigated. The Takagj-Sugeno (T-S) fuzzy model is employed to represent an uncertain nonlinear system with time-delayed state. Then, the parallel distributed compensation technique is used for designing of the robust fuzzy controller. Using a single Lyapunov function, the globally asymptotic stability and disturbance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of robust $H\infty$ controllers are given in terms of linear matrix inequalities via similarity transform and congruence transform technique. We have shown the effectiveness and feasibility of the proposed method through the simulation.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.3 s.234
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• pp.314-321
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• 2005

Discrete Wavelet Transform (DWT) has been applied to the Direct Numerical Simulation (DNS) data of turbulent channel flow. DWT splits the turbulent flow into two orthogonal parts, one corresponding to coherent structures and the other to incoherent background flow. The coherent structure is extracted from not vorticity field but velocity's since the channel flow is not isoropic. By comparing DWT's result of channel flow with that of isotropic flow, it is shown that coherent structure maintains the properties of original channel flow. The velocity field of coherent structures can be represented by few wavelet modes and that these modes are sufficient to reproduce the velocity probability density function (PDF) and the energy spectrum over the entire inertial range. The remaining incoherent background flow is homogeneous, has small amplitude, and is uncorrelated. These results are compared with those obtained for the same compression rate using large eddy simulation (LES) filtering. In contrast to the incoherent background flow of DWT, the LES subgrid scales have a much larger amplitude and are correlated, which makes their statistical modeling more difficult.

• Journal of Ship and Ocean Technology
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• v.9 no.2
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• pp.21-28
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• 2005

Recently moored offshore vessels like as FPSO(Floating Production Storage Offloading) are frequently deployed in seas for a long time. For successful operation, the motion behavior of such a vessel in waves must be clarified in advance either theoretically or experimentally. It is of particular interest to examine the behavior, when swells are superposed to seas with different incident angle. Such a situation is actually reported in some offshore oilfield. In this paper, the motion of a FPSO in irregular waves including swells is studied in time domain. Hydrodynamic coefficients and wave forces are calculated in frequency domain using three-dimensional singularity distribution method. Time memory function and added mass at infinite frequency are derived by Fourier transform utilizing hydrodynamic damping coefficients. In the process, the numerical accuracy of added mass at infinite frequency is carefully examined in association with free decay simulations. It is found from numerical simulations that swells significantly affect the vertical motion of FPSO mainly because of their longer period compared to the ordinary sea waves. In particular, the roll motion is largely amplified because the dominant period of swell is closer to the roll natural period than that of seas.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.5
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• pp.70-77
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• 1999

본 논문에서는 Wavelet을 이용한 위장 영상의 질환 부위 특징을 추출하여 질환 부위 패턴을 인식할 수 있는 알고리즘을 제안하였다. 전처리 과정으로서 위장 영상이 형태정보는 입력 영상을 DWT(Discrete wavelet transform)에 의해 4레벨 DWT 계수 행렬을 구하고 계수 행렬의 특징에 따라 저주파 계수 행렬로부터 저주파 특징 파라미터 32개, 수평 고주파 계수 행렬로부터 수평 고주파 특징 파라미터 16개, 수직 고주파 계수 행렬로부터 수직 고주파 특징 파라미터 16개, 그리고, 대각 고주파 계수 행렬로부터 대각 고주파 특징 파라미터 32개 등 모두 96개의 특징 파라미터를 추출한 후 각각의 특징 파라미터를 최대 값+0.5로 최소 값을 -0.5로 정규화 하여 신경회로망의 입력 벡터로 사용하였다. 위장 영상 패턴 인식을 위한 신경회로망은 교사 학습을 요구하는 다층 구조의 오차 역전파(Error back propagation)알고리즘으로 하였고 구조적 특성을 이용하여 입력층, 중간층, 출력층의 계층 구조로 설계하였다. 설계된 신경회로망의 학습은 학습계수를 0.2로 모우멘텀을 0.6으로 설정하여 출력층 최대오차가 0.01보다 작을 때까지 수행하였으며 약 8000회 정도 학습한 결과 설정값 보다 작은 결과를 얻었고 질환의 종류나 위치, 크기에 관계없이 100%의 인식률을 얻었다.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.55 no.2
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• pp.82-87
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• 2006

Most of electric accidents are happened in the place where activities are frequent by common people who has low electric knowledge. Also, accidents are increased in the low voltage electric equipment. So, it is increased to spread the dispersion or non-utility power generation system. It means that ordinary times observation is required for electric equipments by common people. This paper is studied for the diagnosis method of electric equipment that common people can diagnose easily Voltage is generally and exactly measured in the electric and electronic field. We suggest new analysis tools using only electric voltage. It is called the Time-Energy analysis. The Time-Energy analysis is as following First, divide measured voltage waves into same parts, Second, conducted FFT(Fast Fourier Transform) transform for each divided period, Finally, each results are reassembled after graphic treatment. We compared Time-Energy analysis with discharge form by tracking tester. As the result, tracking discharge processes distinguished clearly.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.670-675
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• 2001

This paper is to propose image segmentation method based on chamfer algorithm. First, we get original image from CCD camera and transform it into gray image. Second, we extract maximum gray value of background and reconstruct and eliminate the background using surface fitting method and bilinear interpolation. Third, we subtract the reconstructed background from gray image to remove noises in gray image. Fourth, we transform the subtracted image into binary image using Otsu's optimal thresholding method. Fifth, we use morphological filters such as areaopen, opening, filling filter etc. to remove noises and isolated points. Sixth, we use chamfer distance or Euclidean distance to this filtered image. Finally, we use watershed algorithm and count microorganisms in image by labeling. To prove the effectiveness, we apply the proposed algorithm to one of Ammonia-oxidizing bacteria, Acinetobacter sp. It is shown that both Euclidean algorithm and chamfer algorithm show over-segmentation. But Chamfer algorithm shows less over-segmentation than Euclidean algorithm.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1813-1818
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• 2004

Discrete Wavelet Transform (DWT) has been applied to the Direct Numerical Simulation (DNS) data of turbulent channel flow. DWT splits the turbulent flow into two orthogonal parts, one corresponding to coherent structures and the other to incoherent background flow. The coherent structure is extracted from not vorticity field but velocity's since the channel flow is not isotropic. By comparing DWT's result of channel flow with that of isotropic flow, it is shown that coherent structure maintains the properties of original channel flow. The velocity field of coherent structures can be represented by few wavelet modes and that these modes are sufficient to reproduce the velocity probability distribution function (PDF) and the energy spectrum over the entire inertial range. The remaining incoherent background flow is homogeneous, has small amplitude, and is uncorrelated. These results are compared with those obtained for the same compression rate using large eddy simulation (LES) filtering. In contrast to the incoherent background flow of DWT, the LES subgrid scales have a much larger amplitude and are correlated, which makes their statistical modeling more difficult.