• Journal of the Institute of Convergence Signal Processing
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• v.14 no.4
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• pp.243-248
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• 2013

In wireless sensor networks, consensus algorithms for dynamic systems may flexibly usable for their data fusion of a sensor network. In this paper, a distributed data fusion filter is implemented using an average consensus based on distributed sensor data, which is composed of some sensor nodes and a sink node to track the mean values of n sensors' data. The consensus filter resolve the problem of data fusion by a distribution Kalman filtering scheme. We showed that the consensus filter has an optimal convergence to decrease of noise propagation and fast tracking ability for input signals. In order to verify for the results of consensus filtering, we showed the output signals of sensor nodes and their filtering results, and then showed the result of the combined signal and the consensus filtering using zeegbee communication.

• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.15-20
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• 2017

Recently, with the development of the IT industry, interest in computer convergence technology is increasing in various fields. Especially, in the semiconductor field, a vision system that uses a camera and computer convergence is often used to inspect semiconductor device defects in the production process. Various systems have been studied to remove noise, which is a major cause of degradation in processing of data related to these image processing systems. In this paper, we try to detect defects in BGA (Ball Grid Array) package devices by recognizing defects in advance during mass production. We propose a measurement system using a Gaussian filter, a Median filter, and an Average filter, which are widely used for noise reduction of image data Applying the proposed system to the manufacturing process of the BGA package can be used to judge whether the defect is good or not, and it is expected that productivity will be improved.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.133-136
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• 2000

에너지 차분 흥부 X선 화상으로부터 폐종류 음영을 검출하기 위한 필터를 예측해서 전문의의 진단보조 혹은 총합자동진단시스템의 구성 요소로서 필터가 발휘한 역할을 고려한 후, 구체적인 성능 평가 방법을 제안한다. 필터의 성능을 평가할 때 문턱값을 변화시킨 경우, 못보고 빠트린 비율과 잘못 본 비율의 변화를 ROC 곡선으로 나타내어 이것에 기초한 판단을 행하는 접근방법이 있다. 본 연구에서는 이와같은 평가에 대한 구체적인 예를 통하여 문제점을 명확히 하여 그 평가기준을 마련한다. 성능 평가를 행하기 위해 이용된 에너지 차분화상으로서, 임상 데이터 14개의 증예를 이용한다. 즉, 총 종류수 32개 한 개의 증예에 있어서 종류의 개수는 1~8개로 평균 2개, 1mm 당 샘플링 간격 5 픽셀, 비트 분해능 10 bit의 저압화상으로, 그 크기는 1760$\times$1760이다. 계산기 하드웨어의 제약으로부터 원화상을 가우스 함수로 평활화 해서 1/8로 축소한 화상으로 실험을 행한다. 상기 평가 절차에 따라, 이전에 개발된 다중해상도 ∇$^2$G 필터의 성능을 평가하고, 단일해상도 ∇$^2$G 필터와의 비교를 통해 그 성능이 우수함을 확인한다. 본 평가 방법은 화상진단 지원용 필터의 평가에 대해서 적용될 수 있을 것이다.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.1
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• pp.33-38
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• 2013

In this paper, we propose an algorithm to track multi-small targets in infrared image sequences in case of dissipation or creation of targets by using the background estimation filter, Kahnan filter and mean shift algorithm. We detect target candidates in a still image by subtracting an original image from an background estimation image, and we track multi-targets by using Kahnan filter and target selection. At last, we adjust specific position of targets by using mean shift algorithm In the experiments, we compare the performance of each background estimation filters, and verified that proposed algorithm exhibits better performance compared to classic methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.06a
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• pp.91-94
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• 2017

본 연구에서는 Component-Substitution (CS)기반 영상 융합 방법 중 가장 빠른 처리 속도를 보이는 IHS 기법의 분광 왜곡 현상을 해결하기 위하여 히스토그램을 통해 분광 왜곡 현상을 분석하고 평균 필터링을 통해 분광 왜곡 현상을 해결한다. 제안하는 방법의 성능 평가를 위하여 아리랑 3 호로 촬영한 서울 지역 위성 영상에 IHS 방법과 제안하는 방법을 적용하여 주관적으로 비교하고 객관적으로는 Q4, SAM, ERGAS 의 지표를 사용하여 비교한다. 주관적 비교 결과 제안하는 방법이 분광 왜곡을 감소시킴을 보이며, 객관적 비교 결과 IHS 기법 대비 향상된 Q4, SAM, ERGAS 을 보인다.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.151-156
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• 2010

This paper is a study on image noise reduction of modified sigma filter by image decomposition using directivity. Conventional sigma filter has been shown to be a good solution both in terms of filtering accuracy and computational complexity. However, the sigma filter does not preserve well small edges especially for high level of additive noise. In this paper, we propose here a new method using a modified sigma filter. In our proposed method the input image is first decomposed in two components that have features of horizontal, vertical and diagonal direction. Then, two components are applied HPF and LPF. By applying a conventional sigma filter separately on each of them, the output image is reconstructed from the filtered components. Added noise is removed and our proposed method preserves the edges from the image. Comparative results from experiments show that the proposed algorithm achieves higher gains, on average, 2.6 dB PSNR than the sigma filter and 0.5 dB PSNR than the modified sigma filter. When relatively high levels of noise added, the proposed algorithm shows better performance than two conventional filters.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.1
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• pp.29-35
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• 2016

This paper presents an analysis of the short-range radar noise adjusting the angle of the radar reflector for the handicapped aids and suggests a complementary filter that combines a moving average filter with a heuristic algorithm to remove the radar noise. It also shows the effectiveness of the suggested filter by comparing the experiments results between the Kalman filter and the suggested filter.

• Journal of IKEEE
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• v.18 no.3
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• pp.376-382
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• 2014

In this paper, we propose a advanced attitude PID controller and sensor fusion method robust to the vibration of the quadcopter unmanned air vehicle using four BLDC motors. When the gyro sensor and acceleration sensor are fused, a complementary filter is designed to ignore the vibrations generated by the motors and to complement the drawbacks. As a result, we obtain accurate results than using each sensor. Also, it is possible to obtain a low delay results in robust to vibration than the low-pass filter or moving average filter, which is generally used for quadcopter. And we improved D controller, which have being used for attitude control of quadcopter, to quadcopter using gyro sensor. it was confirmed that the attitude is stabilized and error is reduced By using gyro sensor output instead of variation of estimated angle in D control.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.93-96
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• 2006

회전 기계(Rotor)는 여러 분야의 산업 현장에서 중요한 역할을 하는 기기중 하나로 운전 중인 회전 기계의 동작, 감시, 진단은 설비의 효율적인 운용 및 사고 방지 등을 위해 매우 중요한 일이다. 본 논문에서는 회전 기계 중 가장 널리 사용되는 유도 전동기의 운전 중 발생하는 정상 신호와 이상 신호들의 특징을 비교 분석하고 그 결과를 바탕으로 스펙트럼 평균, 고역 통과 필터, 대역 통과 필터, 스펙트럼 밀도 등을 적용하여 이상 신호를 검출하고 진단하는 시스템을 구성하였으며 알고리듬 시뮬레이션 결과 올바로 분류된 결과를 얻을 수 있었다.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.2
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• pp.30-36
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• 2002

This paper describes a nonlinear adaptive noise canceler(ANC) using neural networks(NN) based on filter to make up for the drawback of the conventional ANC with the linear adaptive filter. The proposed ANC was tested its noise rejection performance using broadband time-varying noise signal and compared with the ANC of TDL linear filter. Experimental results show that in cases of nonlinear correlations between the noise of primary input and reference input, the neural network based ANC outperforms the linear ANC with respect to mean square error It is also verified that the recurrent NN adaptive filter is superior to the feedforward NN filter. Thus, we identify that the NN adaptive filter is more effective than the linear adaptive filter for rejection of broadband time-varying noise in the ANC.