• Journal of Korea Multimedia Society
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• v.12 no.4
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• pp.600-607
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• 2009

In order to obtain continuous navigation information at low cost, we demonstrate, in this work, a position system which is constructed by integrating accelerometers with GPS. The proposed system eliminates vibration and noise elements of accelerometers by using Kalman filter. Calculating continuous navigation information is executed by unifying GPS position data and accelerations of moving and centripetal directions which affect the vehicle. Through simulations and experiments, we show that the performance of GPS can be improved by employing accelerometers. Our proposed system can provide stable and seamless position information where the GPS signal is unavailable due to obstruction like tunnels, and high buildings. The designed system can be implemented at low cost of circuit design and production, and satisfy various installation conditions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.173-181
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• 1995

통계적 공정관리 분야가 점차 컴퓨터를 이용한 관리를 하게 되므로써 공정관리의 온라인화, 실시간화가 되고 있는 가운데, 기존의 관리도는 공정의 파라미터를 기지의 상수값으로 간주하므로 모형이 잘못 설정되었을 경우 상당히 많은 오보(false alarm)를 발생하게 된다. 이에 본 연구는 연속생산공정에서, 칼만필터를 적용하여 공정의 불확실한 파라미터와 모형의 오차에도 불구하고 공정의 변화를 보다 빠르고 정확하게 탐지할 수 있는 관리도를 설계하였다. 본 연구에서 설계한 관리도는 관축치들간에 시간적 종속성이 존재하는 경우에 있어서, 관측치들을 시계열모형으로 묘사를 하여, 파라미터(parameter)를 추정하고, 잔차를 얻어서 만든 잔차관리도로서, 실시간으로 생산공정을 관리하는 경우 효과적임을 보이기 위하여, 컴퓨터 시뮬레이션을 통해 ARL을 구하여 기존에 사용되고 있는 관리도와 수행도를 비교.평가하였다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.6
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• pp.47-53
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• 2004

This paper proposes an algerian for determining robot location using appearance-based paradigm. First, this algorithm compresses the image set using Principal Component Analysis(PCA) to obtain a low-dimensional subspace, called the eigenspace, and it makes a manifold that represent a continuous-appearance function. Neural network is employed to estimate the location of the mobile robot from the coefficients of the eigenspace. Then, Kalman filtering scheme is used for the fine estimation of the robot location. The algorithm has been implemented and tested on a mobile robot system. It is shown that the robot location is estimated accurately in several trials.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.407-410
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• 2009

본 논문에서는 개선된 mean shift를 이용한 컬러 영상 분할을 소개한다. Mean shift는 Yizong Cheng에 의해 재조명되고 Dorin Comaniciu 등에 의해 정리되어 영상 필터링(image filtering), 영상 분할(image segmentation), 물체 추적(object tracking) 등 여러 응용 분야에 널리 활용되고 있다. 커널을 이용해 밀도를 추정하고 밀도가 가장 높은 점으로 커널을 연속적으로 이동함으로써 지역적으로 주요한 위치로 데이터 값을 갱신시킨다. 그러나 영상에 포함된 모든 화소에 대해 mean shift를 수행해야하기 때문에 연산 시간이 많이 소요되는 단점이 있다. 본 논문에서는 mean shift 필터링 과정을 분석하고 참조수렴방법과 강제수렴방법을 이용해 소요 시간을 단축시켰다. 모든 점에 대해 mean shift를 수행하는 대신 특정 조건을 만족하는 픽셀은 이웃 픽셀의 수렴 값을 참조하고, mean shift 과정에 진동 또는 미미한 이동을 계속하는 픽셀은 강제 수렴을 실시하였다. 개선된 방법과 기존의 mean shift 방식을 적용하여 영상 필터링과 영상 분할에 적용한 실험에서 결과 영상에는 차이가 적고 기존의 방법에 비해 수행 시간이 24% 정도 소요됨을 확인하였다.

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.305-317
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• 2006

Outliers adversely affect model identification, parameter estimation, and forecast in time series data. In particular, when outliers consist of a patch of additive outliers, the current outlier detection procedures suffer from the masking and swamping effects which make them inefficient. In this paper, we propose new outlier detection procedure based on high breakdown estimators, called as the dual robust filtering. Empirical and simulation studies in the autoregressive model with orders p show that the proposed procedure is effective.

• Geophysics and Geophysical Exploration
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• v.15 no.2
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• pp.51-56
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• 2012

One of the most critical and essential procedures in the interpretation of gravity and magnetic data is to separate the anomaly due to the specific geologic structure from the summation of effects from a broad variety of geologic sources, especially those of different depths. Separation of the residual anomaly from the regional field is the most simple case of the vertical separation. If the anomaly due to a layer of specific depth can be separated or the depth of the separated layer can be quantitatively determined, it may deserve the separation-sounding. We suggest a wavelength filter whose cutoff frequency is determined by log-power spectrum analysis, as a separation-sounding filter. We applied this filter both to synthetic and real gravity data acquired at Heunghae area, and compared the results with those of Jacobsen's upward continuation filter. These showed that the proposed separation-sounding filter could be a useful tool for interpretation of the vertical geologic structure by stripping the gravity effects of geologic sources down to the desired depth.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.584-591
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• 2007

The recognition of human gestures in image sequences is an important and challenging problem that enables a host of human-computer interaction applications. This paper describes a gesture recognition algorithm based on the particle filters, namely CONDENSATION. The particle filter is more efficient than any other tracking algorithm because the tracking mechanism follows Bayesian estimation rule of conditional probability propagation. We used two models for the evaluation of particle filter and apply the MAILAB for the preprocessing of the image sequence. But we implement the particle filter using the C++ to get the high speed processing. In the experimental results, it is demonstrated that the proposed algorithm prove to be robust in the cluttered environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2032-2038
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• 2006

The recognition of human gestures in image sequences is an important and challenging problem that enables a host of human-computer interaction applications. This paper describes a gesture recognition algorithm based on the particle filters, namely CONDENSATION. The particle filter is more efficient than any other tracking algorithm because the tracking mechanism follows Bayesian estimation rule of conditional probability propagation. We used two models for the evaluation of particle Inter and apply the MATLAB for the preprocessing of the image sequence. But we implement the particle filter using the C++ to get the high speed processing. In the experimental results, it is demonstrated that the proposed algorithm prove to be robust in the cluttered environment.

• Journal of Broadcast Engineering
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• v.20 no.2
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• pp.265-272
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• 2015

A new technology on video frame rate up-conversion (FRUC) is presented by combining the median filter and motion estimation (ME) with an occlusion detection (OD) method. First, ME is performed to have a motion vector. Then, the OD method is used to refine motion vector in the occlusion region. Since the wrong motion vector can be obtained with high possibility in the occluded area, a median filtering that less depends on the motion vector is applied to that area, and since the motion vector is continuous and robust in the non-occluded area, BDMC(Bi-Directional Motion Compensated interpolation) is applied to obtain interpolated image in that area. BDMC using the bi-directional motion vectors achieves good results when continuity and robustness of the motion vector is higher. Experimental results show that the proposed algorithm provides better performance than the conventional approach. The average gain of PSNR (Peak Signal to Noise Ratio) is approximately 0.16 dB in the test sequences compared with BDMC.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.361-363
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• 2004

시간 및 주파수 특성 분석이 용이한 웨이블릿을 신경회로망에 적용시킨 웨이블릿 신경 회로망의 파라미터 학습 방법에는 오차 역전파 알고리듬 및 유선 알고리듬 등 여러 가지 방법이 있으나 이러한 학습 방법들은 수렴 시간이 오래 걸리는 단점을 가진다. 따라서 본 논문에서는 웨이블릿 신경 회로망의 최적 파라미터를 결정하기 위한 학습 방법으로 일반적으로 비선형 시스템 추정에 주로 사용되는 확장 칼만 필터 알고리듬을 적용한 신경회로망을 제안한다. 또한 제안된 학습 알고리듬을 이용한 웨이블릿 신경 회로망으로 간접 적응 제어기를 설계하여 연속 시간 혼돈 시스템인 Duffing 시스템의 제어에 적용함으로써 확장 칼만 필터 학습 알고리듬을 적용한 웨이블릿 신경 회로망 모델의 우수성을 보인다.