• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.756-763
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• 2013

Bilateral filter (BF), functioning by two Gaussian filters, domain and range filter is a nonlinear filter for sharpness enhancement and noise removal. In infrared (IR) small target detection field, the BF is designed by background predictor for predicting background not including small target. For this, the standard deviations of the two Gaussian filters need to be changed adaptively in background and target region of an infrared image. In this paper, the proposed bilateral filter make the standard deviations changed adaptively, using variance feature of mean values of surrounding block neighboring local filter window. And, in case the variance of mean values for surrounding blocks is low for any processed pixel, the pixel is classified to flat background and target region for enhancing background prediction. On the other hand, any pixel with high variance for surrounding blocks is classified to edge region. Small target can be detected by subtracting predicted background from original image. In experimental results, we confirmed that the proposed bilateral filter has superior target detection rate, compared with existing methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.163-164
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• 2018

본 논문에서는 양방향 예측 모드에서 LIC(Local Illuminance Compensation)의 복잡도 감소를 위한 방법을 제안한다. 제안하는 방법은 현재 CU 가 양방향 예측 모드일 경우 움직임 보상 단계에서 예측 블록 두 개를 가중 평균을 낸 뒤 LIC 를 수행함으로써 양방향 예측모드에서 LIC 를 한번만 수행하여 기존 LIC 대비 낮은 복잡도를 보인다. 제안하는 방법의 성능 평가를 위하여 RA(Random Access) 조건에서 MPEG 표준 실험 영상의 B, C, D 클래스를 이용하여 BD-rate 를 VTM-2.0.1 과 비교한다. 실험결과로서 본 논문에서 제안하는 방법이 VTM2.0.1 대비 BD-rate 성능 관점에서 Y, U, V 각각에 대하여 평균 0.17, 0.17, 0.23 의 성능 향상을 보인다.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.746-755
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• 2013

This paper presents a three dimensional bilateral filter detecting target trajectory, extracting spatial target information using two dimensional bilateral filter and temporal target information using one dimensional bilateral filter. In order to discriminate edge pixel with flat background and target region spatially and temporally, spatial and temporal variance are used for an image and temporal profile. With this procedure, background and background profile are predicted without original target through two dimensional and one dimensional bilateral filter. Finally, using spatially predicted background and temporally predicted background profile, small target can be detected. For comparison of existing target detection methods and the proposed method, the receiver operating characteristics (ROC) is used in experimental results. Experimental results show that the proposed method has superior target detection rate and lower false alarm rate.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.1-7
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• 2005

We propose an effective Landsat TM image compression method using the classified bidirectional prediction (CBP), the classified KLT and the SPIHT. The SPIHT is used to exploit the spatial redundancy of feature bands selected in the visible range and the infrared range separately. Regions of the prediction bands are classified into three classes in the wavelet domain, and then the CBP is performed to exploit the spectral redundancy. Residual bands that consist of difference values between the original band and the predicted band are decorrelated by the spectral KLT Finally, the three dimensional (3-D) SPIHT is used to encode the decorrelated coefficients. Experiment results show that the proposed method reconstructs higher quality Landsat TM image than conventional methods at the same bit rate.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.605-607
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• 2018

본 논문에서는 음절 임베딩과 양방향 LSTM-CRF 모델을 이용한 한국어 문장 자동 띄어쓰기 시스템을 제안한다. 문장에 대한 자질 벡터 표현을 위해 문장을 구성하는 음절을 Unigram 및 Bigram으로 나누어 각 음절을 연속적인 벡터 공간에 표현하고, 양방향 LSTM을 이용하여 현재 자질에 양방향 자질들과 의존성을 부여한 새로운 자질 벡터를 생성한다. 이 새로운 자질 벡터는 전방향 신경망과 선형체인(Linear-Chain) CRF를 이용하여 최적의 띄어쓰기 태그 열을 예측하고, 생성된 띄어쓰기 태그를 기반으로 문장 자동 띄어쓰기를 수행하였다. 문장 13,500개와 277,718개 어절로 이루어진 학습 데이터 집합과 문장 1,500개와 31,107개 어절로 이루어진 테스트 집합의 학습 및 평가 결과는 97.337%의 음절 띄어쓰기 태그 분류 정확도를 보였다.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.4
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• pp.389-394
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• 2002

In this paper, we propose a robust stereo matching algorithm using nonlinear extended Kalman filter. The proposed algorithm estimates disparity using nonlinear extended Kalman filter and compares left image to right image for obtained disparity. As this process is run iteratively, we get disparity only with a few search. And, we can get robust stereo matching results by comparing left image to right image using bilinear interpolation to consider influence of neighborhood pixel. We compared SSD algorithm which is widely used, in stereo matching method, to result of the proposed algorithm. As the result, the proposed algorithm has an outstanding matching performance.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.1-8
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• 2012

Video FRUC (Frame Rate Up Conversion) has been a technique of great interest due to its diversified applications in consumer electronics. Most advanced FRUC algorithms adopt a motion interpolation technique to determine the motion vector field of interpolated frames. But, in some applications, it is necessary to evaluate how well the MCI (Motion Compensated Interpolation) frame is reconstructed. For this aim, this paper proposes a distortion estimation for motion compensated interpolation frame using frame-adaptive distortion estimation. The proposed method is applied for the symmetric motion estimation and compensated scheme and then analyzed by three different approaches, that is, forward estimation, backward estimation and adaptive bi-directional estimation schemes. Through computer simulations, it is shown that the proposed bi-directional estimation method outperforms others and can be effectively applied for FRUC.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.463-471
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• 2019

This paper proposes a method for reducing the complexity of LIC (Local Illuminance Compensation) for bi-directional inter prediction. The LIC performs local illumination compensation using neighboring reconstruction samples of the current block and the reference block to improve the accuracy of the inter prediction. Since the weight and offset required for local illumination compensation are calculated at both sides of the encoder and decoder using the reconstructed samples, there is an advantage that the coding efficiency is improved without signaling any information. Since the weight and the offset are obtained in the encoding prediction step and the decoding step, encoder and decoder complexity are increased. This paper proposes two methods for low complexity LIC. The first method is a method of applying illumination compensation with offset only in bi-directional prediction, and the second is a method of applying LIC after weighted average step of reference block obtained by bidirectional prediction. To evaluate the performance of the proposed method, BD-rate is compared with BMS-2.0.1 using B, C, and D classes of MPEG standard experimental image under RA (Random Access) condition. Experimental results show that the proposed method reduces the average of 0.29%, 0.23%, 0.04% for Y, U, and V in terms of BD-rate performance compared to BMS-2.0.1 and encoding/decoding time is almost same. Although the BD-rate was lost, the calculation complexity of the LIC was greatly reduced as the multiplication operation was removed and the addition operation was halved in the LIC parameter derivation process.

• Journal of Korean Society of Transportation
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• v.16 no.2
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• pp.133-144
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• 1998

양방향 2차로 도로는 우리나라 전체 포장도로 연자의 84%를 차지하고 있다. 양방향 2차로 도로의 효율성 및 교통류의 운영상태를 파악하기 위한 서비스 수준 척도로 지체시간의 백분율이 많이 사용되고 있다. 지체시간의 산정은 특정 도로 설계구간을 추원금지구간으로 설계할 것이지, 예산을 더 투자하여 선형을 개선함으로써 추원가능 구간으로 설계할 것인지에 대한 판단 기준을 제시할 수 있기 때문에 도로설계과정에 있어서 매우 중요하다. 본 연구에서는 저속차량의 확률적 분포를 고려하여 추원금지구간에서 발생하는 지체시간을 산정할 수 있는 모형을 제시하였다. 모형식이 기존에 확률적 분포를 고려하여 추월금지구간에서 발생하는 지체시간을 산정할 수 있는 모형을 제시하였다. 모형식이 기존에 개발된 거시적 수학적 모형에 비해 비교적 단순하고 입력변수도 수집이 용이한 점이 특징이라 할 수 있다. 모형의 신뢰성을 현장데이터를 이용하여 검증한 결과, 모혀으이 예측값이 근사적으로 츠덩한 실제 지체시간을 포함하는 긍정적인 결과를 도출하였다. 그러나 모형의 예측값 범위가 넓어 실용적인 MOE로 사용하기에 다소 무리가 있을 것으로 판단되므로, 개략적인 평가기준으로 모형이 예측한 값의 평균값을 보정하여 사용할 것을 제안한다. 모형의 신뢰성을 높이기 위해서는 본 연구에서 가정한 확률분포식에 대한 추가적인 검증이 필요할 것으로 판단된다. 본 연구는 실제 상황을 표현하는데 있어 확률적 개념의 도입과 이러한 새로운 접근방법의 기초를 마련한 측면에서 의미를 갖는다. 또한, 양방향 2차로 도로에서의 지체시간은 실제 소요시간과 자유운행시 즉 다른 차량의 영향을 받지 않았을 때의 속도 및 운영시간과의 차이로 정의한 바, 실제 지체시간을 현장자료를 통해 구하기란 현실적으로 불가능하므로, 본 연구에서는 이러한 제약점을 극복할 수 있는 근사적인 지체시간을 계산하는 방법을 제시한 점에서 의미를 갖을 수 있다.

• Journal of IKEEE
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• v.23 no.1
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• pp.254-260
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• 2019

The failure rate of bidirectional dc-to-dc converter is predicted through the failure mode and effect analysis (FMEA) and the fault-tree analysis (FTA) considering the operational risk. In order to increase the driving voltage of the electric vehicle efficiently, the bidirectional converter is attached to the front of the inverter. It has a boost mode for discharging battery power to the dc-link capacitor and a buck mode for charging the regenerative power to the battery. Based on the results of the FMEA considering the operating characteristics of the bidirectional converter, the fault-tree is designed considering the risk of the converter. After setting the design parameters for the MCU for the electric vehicle, we analyze the failure rate of the capacitor due to the output voltage ripple and the inductor component failure rate due to the inductor current ripple. In addition, we obtain the failure rate of major parts according to operating temperature using MIL-HDBK-217F. Finally, the failure rate and the mean time between failures (MTBF) of the converter are predicted by reflecting the part failure rate to the basic event of the fault-tree.