• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.4
• /
• pp.771-781
• /
• 1997

In order to solve the problem of uncovered background region due to the region-due to the region-based motion estimation, this paper presents a new method which generates the uncovered region memory using motion estimation and shows the application of the algorithm for very low bit rate video coding. The proposed algorithm can be briefly described as follows it detects the changed region by using the information of FD(frame difference) and segmentation, and then as for only that region the backward motion estimation without transmission of shape information is done. Therefore, from only motion information the uncovered background region memory is generated and updated. The contents stored in the uncovered background region memory are referred whenever the uncovered region comes into existence. The regions with large prediction error are transformed and coded by using DCT. As results of simulation, the proposed algorithm shows the superior improvement in the subjective and objective image quality due to the remarkable reduction of transmission bits for prediction error.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2010.05a
• /
• pp.125-126
• /
• 2010

• Journal of the Korean Statistical Society
• /
• v.34 no.3
• /
• pp.197-208
• /
• 2005

We consider the problem for approximate solution of linear stochastic evolution equations driven by infinite-dimensional fractional Brownian motion with Hurst parameter $H\;\in$ (0,1/2). The error of the approximate solution for the explicit Euler scheme is investigated.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2011.06a
• /
• pp.129-130
• /
• 2011

• International Journal of Aeronautical and Space Sciences
• /
• v.18 no.1
• /
• pp.118-128
• /
• 2017

In this study, we propose a real time inertial navigation system/global positioning system (INS/GPS) integrated smoothing algorithm based on an extended Kalman filter (EKF) and a position damping loop (PDL) for synthetic aperture radar (SAR). Integrated navigation algorithms usually induce discontinuities due to error correction update by the Kalman filter, which are as detrimental to the performance of SAR as the relative position error. The proposed smoothing algorithm suppresses these discontinuities and also reduces the relative position error in real time. An EKF estimates the navigation errors and sensor biases, and all the errors except for the position error are corrected directly and instantly. A PDL activated during SAR operation period imposes damping effects on the position error estimates, where the estimated position error is corrected smoothly and gradually, which contributes to the real time smoothing and small relative position errors. The residual errors are re-estimated by the EKF to maintain the estimation performance and the stability of the overall loop. The performance improvements were confirmed by Monte Carlo simulations. The simulation results showed that the discontinuities were reduced by 99.8% and the relative position error by 48% compared with a conventional EKF without a smoothing loop, thereby satisfying the basic performance requirements for SAR operation. The proposed algorithm may be applicable to low cost SAR systems which use a conventional INS/GPS without changing their hardware configurations.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.17 no.1
• /
• pp.106-112
• /
• 2008

In this paper, It does the profile measurement of the cam of diesel engine SOHC of the actual object. It uses the measurement of run-out method. This method is that the surface of the object is measured by the sensor when the object rotate, and calculated and displayed by the computer the signal which acquired by sensor. When we acquire the signals, we have two error because of motion and contacting between cam and probe. In this paper, we compensate the motion error while simply liner equation. And we have a solution that we change the figure of probe when we have a contacting error. We compared the data measuring on developed automatic cam profile measuring system with the data measured on CMM.

• Journal of Broadcast Engineering
• /
• v.23 no.5
• /
• pp.628-635
• /
• 2018

In this paper, we propose a fast motion estimation algorithm which is important in video encoding. So many fast motion estimation algorithms have been published for improving prediction quality and computational reduction. In the paper, we propose an algorithm that reduces unnecessary computation, while almost keeping prediction quality compared with the full search algorithm. The proposed algorithm calculates the sum of partial block matching error for each candidate, selects the candidates for the next step, compares the stability of optimal candidates with minimum error, and finds optimal motion vectors by determining the progress of the next step. By doing that, we can find the minimum error point as soon as possible and obtain fast computational speed by reducing unnecessary computations. Additionally, the proposed algorithm can be used with conventional fast motion estimation algorithms and prove it in the experimental results.

• Korean Journal of Applied Biomechanics
• /
• v.27 no.1
• /
• pp.53-58
• /
• 2017

Objective: The purpose of this study was to compare the accuracy of stride time and stride length provided by a commercial APDM inertial sensor system (APDM) with the results of three dimensional motion capture system (3D motion) during treadmill walking. Method: Five healthy men participated in this experiment. All subjects walked on the treadmill for 3 minutes at their preferred walking speed. The 3D motion and the APDM were simultaneously used for extracting gait variables such as stride time and stride length. Mean difference and root mean squared (RMS) difference were used to compare the measured gait variables from the two measurement devices. The regression equation derived from the range of motion of the lower limb was also applied to correct the error of stride length. Results: The stride time extracted from the APDM was almost the same as that from the 3D motion (the mean difference and RMS difference were less than 0.0001 sec and 0.0085 sec, respectively). For stride length, mean difference and RMS difference were less than 0.1141 m and 0.1254 m, respectively. However, after correction of the stride length error using the derived regression equation, the mean difference and the RMS difference decreased to 0.0134 m and 0.0556 m or less, respectively. Conclusion: In this study, we confirmed the possibility of using the temporal variables provided from the APDM during treadmill walking. By applying the regression equation derived only from the range of motion provided by the APDM, the error of the spatial variable could be reduced. Although further studies are needed with additional subjects and various walking speeds, these results may provide the basic data necessary for using APDM in treadmill walking.

• Journal of the Institute of Convergence Signal Processing
• /
• v.18 no.2
• /
• pp.62-67
• /
• 2017

In this paper, we propose a fast motion estimation algorithm which is important in performance of video encoding. Even though so many fast algorithms for motion estimation have been published due to tremendous computational amount of full search algorithm, efforts for reducing computations of motion estimation still remain. In the paper, we propose an algorithm that reduces unnecessary computations only, while keeping prediction quality the same as that of the full search. The proposed algorithm does not calculate block matching error for each candidate directly to find motion vectors but divides the calculation procedure into several steps and calculates partial sum of block errors for candidates with high priority. By doing that, we can find the minimum error point early and get the enhancement of calculation speed by reducing unnecessary computations. The proposed algorithm uses smaller computations than conventional fast search algorithms with the same prediction quality as the full search algorithm.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.8
• /
• pp.29-39
• /
• 2015

This paper describes a design and implementation of fuzzy-based algorithm for hand-shake state detection and error compensation in the mobile optical image stabilization(OIS) motion detector. Since the gyro sensor output of the OIS motion detector includes inherent error signals, accurate error correction is required for prompt hand-shake error compensation and stable hand-shake state detection. In this research with a little computation overhead of fuzzy-based algorithm, the hand-shake error compensation could be improved by quickly reducing the angle and phase error for the hand-shake frequencies. Further, stability of the OIS system could be enhanced by the hand-shake states of {Halt, Little vibrate, Big vibrate, Pan/Tilt}, classified by subdividing the hand-shake angle. The performance and stability of the proposed algorithm in OIS motion detector is quantitatively and qualitatively evaluated with the emulated hand-shaking of ${\pm}0.5^{\circ}$, ${\pm}0.8^{\circ}$ vibration and 2~12Hz frequency. In experiments, the average error compensation gain of 3.71dB is achieved with respect to the conventional BACF/DCF algorithm; and the four hand-shake states are detected in a stable manner.