• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.185-187
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• 2008

Speckle noise is primarily due to the phase fluctuations of the electromagnetic return signals. Since inherent spatial-correlation characteristics of speckle in SAR images are not exploited in existing multiplicative models for speckle noise. In this paper, we investigate the efficiency of the filters: Kuan, Gamma, Enhanced Lee, and Enhanced Frost filters in reduction of speckle noise in forestry area. Selection of the suitable filter can be played an important role in applications such as estimation of biomass in forestry areas. We employ ALOSPALSAR image use L-band frequency for this investigation. The filters test on different sites in PALSAR image of the northern forests part of Iran.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.355-358
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• 2005

Fingerprint recognition systems are the most widely used in biometrics for personal authentication. As they become more familiar, the security weaknesses of fingerprint sensors are becoming better known. In this paper, we propose a liveness detection method that applies correlation filter to the fingerprint recognition systems. The physiological characteristic of sweat pore, observed only in live people, is used as a measure to classify 'live' fingers from 'spoof' fingers. Previous works show that detection of sweat pores and perspiration patterns in fingerprint images can be used as an anti-spoofing measure. These methods don't consider the characteristic of pores in each individual. We construct the correlation filters of each individual which are composed of their pore information. We make the final decision about the "livens" of fingerprint using correlation output. The proposed algorithm was applied to a data set of 110 live, 110 spoof fingerprint images from optical fingerprint scanner and achieved classification rate of 80%.

• Journal of the Optical Society of Korea
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• 제20권2호
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• pp.257-262
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• 2016

A two-dimensional optical code division multiple access (OCDMA) en/decoder composed of four double-ring resonator add/drop filters and three delay waveguides is designed, and a transfer matrix method combined with fast Fourier transform is implemented to provide numerical simulations for the en/decoder. The auto-correlation peak level over the maximum cross-correlation level is larger than 3 at the center of the correctly decoded pulse for most of wavelength hopping and spectral phase code combinations, which assures the BER lower than 10^-3 which corresponds to the forward error correction limit.

• 한국정밀공학회지
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• 제24권11호
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• pp.76-83
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• 2007

The dark-field laser scattering system has been developed to inspect surface defects in infrared cut-off filters and then laser scattering characteristics against the defects are investigated. The qualitative analysis for the reliable and accurate detection performance is described through the correlation between incident angles of a laser and viewing ones of a camera. In this paper, reliable and important information with laser scattering is given for the surface defect inspection of IR filters. Its performance has been verified through various experiments.

• 한국컴퓨터정보학회논문지
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• 제25권7호
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• pp.57-64
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• 2020

본 논문에서는 상관필터를 이용한 영상 추적에서 탐색 영역의 크기 조절이 가능한 재탐지 방법을 제안한다. 실제 장비를 통해 영상 추적 기능을 실행할 때에는 표적이 특정 물체에 가리고 다시 나타나는 일이 빈번하게 일어나는데, 따라서 표적의 소실 판단과 재탐지 방법이 필요하다. 본 알고리즘은 강인한 추적을 위해 커널 상관필터를 사용한다. 일반적인 상관필터를 활용한 영상 추적 알고리즘에서는 표적을 탐지하는 범위가 학습된 필터의 크기에 국한된다. 하지만 표적의 가림이 오랜 시간 지속될수록 표적의 위치는 예측된 위치에서 벗어날 가능성이 커지고, 따라서 충분히 큰 범위에서 표적의 탐색이 이루어져야 한다. 제안하는 방법은 매 프레임 2%씩 탐색 범위를 넓히며 재탐지를 시도하여 성공률을 높인다. 실험은 항공에서 촬영된 4가지 영상을 활용하였고, 제안한 알고리즘은 재탐지가 어려운 데이터셋에서도 성공적인 결과를 보였다.

• 한국멀티미디어학회논문지
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• 제4권3호
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• pp.230-237
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• 2001

음향 반향 제거기, 적응 등화기 그리고 적웅 잡음 제거기 등에 적응 필터가 널리 활용되고 있다. 적응 필터의 계수는 주로 NLMS 알고리즘을 이용하고 있지만 NLMS 알고리즘은 주변 잡음에 의해서 적응 필터의 계수가 오조정된다. 본 논문에서 최적 필터의 직교원리를 이용하여 LMS 알고리즘의 순시 기울기 벡터를 저역 통과 시켜 적응 알고리즘의 적응 상수로 결정하는 방법을 제안한다. 순시 기울기 벡터는 입력 신호와 추정 오차 신호의 상호 상관도로써 수렴 초기에는 추정 오차 신호 속에 입력 신호가 대부분 포함되어 있기 때문에 상관도가 크고 적응 필터가 수렴한 후에는 0 에 가까운 값을 갖게 된다. 그리고 입력 신호와 주변 잡음 신호는 상관이 없기 때문에 주변 잡음에 의해서 상호 상관도는 큰 변화가 없다. 따라서 상호 상관도를 적응 상수로 결정하면 수렴 속도가 느려지지 않으면서 주변 잡음에 강건한 특성을 가진다. 본 논문에서는 컴퓨터 시뮬레이션을 통해서 제안하는 적응 알고리즘의 성능이 기존 알고리즘에 비해서 우수함을 보인다.

• Journal of Korean Society for Atmospheric Environment
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• 제23권E2호
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• pp.66-73
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• 2007

The introduction of tracer gas techniques to ventilation studies in indoor environments provides valuable information that used to be unattainable from conventional testing environments. Data acquisition systems (DASs) containing analogue-to-digital (A/D) converters are usually used to function the key role that records signals to storage in digital format. In the testing process, there exist a number of components in the measuring equipment which may produce system-based inference to the monitored results. These unwanted fluctuations may cause significant error in data analysis, especially when non-linear algorithms are involved. In this study, a pre-processor is developed and applied to separate the unwanted fluctuations (noise or interference) in raw measurements and to reduce the uncertainty in the measurement. Moving average, notch filter, FIR (Finite Impulse Response) filters, and IIR (Infinite Impulse Response) filters are designed and applied to collect the desired information from the raw measurements. Tracer gas concentrations are monitored during leakage and ventilation tests in the model test room. The signal analysis functions are introduced to carry out the digital signal processing (DSP) work. Overall the FIR filters process the $CO_2$ measurement properly for ventilation rate and mean age of air calculations. It is found that, the Kaiser filter was the most applicable digital filter for pre-processing the tracer gas measurements. Although the IIR filters help to reduce the random noise in the data, they cause considerable changes to the filtered data, which is not desirable.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 F
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• pp.2549-2552
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• 1999

The fictitious power theory in time domain is very easy to understand, but power analyzing time of active power is increased, because power is analyzed using signal techniques based on the correlation between voltage and current waveforms. Also, conventional methods in time/frequency domain to evaluate the compensation performance of active power filters are not provided easy solutions. So, the authors have previously proposed 3-D current coordinates which is composed into active component, fundamental reactive component and distorted component of nonlinear loads current. This method has excellent performance, but can not evaluate the characteristics of nonlinear load current whether inductive or capacitive. Therefore, To overcome problems mentioned previously, this paper deals with the simple instantaneous power theory and the modified 3-D current coordinates for evaluating the compensation performance of active power filters. To confirm the validity, active power filters simulator is developed using C-language. From the simulation, results are discussed their utility.

• 한국통신학회논문지
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• 제19권12호
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• pp.2364-2375
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• 1994

효율적인 인쇄체 한글 인식을 위하여 다중 최소평균 상관 에너지 필터를 제안하였다. 제안된 방법은 기존의 나무구조 알고리듬의 단점인 인식시스템의 방대함과 인식방법의 복잡함을 해결하였다. 오직 하나의 자음 MMACE 필터와 모음 MMACE 필터를 사용하여 완전한 한글을 인식하였다. 각 MMACE 필터는 24개의 자모음으로 합성된 4개의 K-tuple MACE 필터를 이용하여 다중화시켰다. 따라서 제안된 MMACE 필터의 필터평면과 상관분포 평면은 4개의 부평면으로 나누어 진다. 각 상관분포 부평면으로 한글 인식을 위한 코드를 얻었다. 얻어진 코드와 컴퓨터에 내장된 자모음을 인식하기 위한 진리표와 비교하였다. 일치하는 코드의 해당자모음을 찾아 출력상관평면상의 상관첨두 위치에 치환하면 완전한 한글을 인식할 수 있다. 컴퓨터 시뮬레이션과 광 실험을 통하여 제안된 MMACE 필터를 이용한 한글 인식 시스템의 높은 변별력을 확인하였다.

• ETRI Journal
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• 제36권1호
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• pp.99-105
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• 2014

This paper presents a new locomotion mode recognition method based on a transformed correlation feature analysis using an electromyography (EMG) pattern. Each movement is recognized using six weighted subcorrelation filters, which are applied to the correlation feature analysis through the use of six time-domain features. The proposed method has a high recognition rate because it reflects the importance of the different features according to the movements and thereby enables one to recognize real-time EMG patterns, owing to the rapid execution of the correlation feature analysis. The experiment results show that the discriminating power of the proposed method is 85.89% (${\pm}2.5$) when walking on a level surface, 96.47% (${\pm}0.9$) when going up stairs, and 96.37% (${\pm}1.3$) when going down stairs for given normal movement data. This makes its accuracy and stability better than that found for the principal component analysis and linear discriminant analysis methods.