• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.9
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• pp.109-117
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• 1997

A new relaxation algorithm based on distribution of matched errors and possibility is proposed to solve efficiently correspondence problem. This algorithm can be applied to various method, such as BMA, feature-, and region-based matching methods, by modifying its smoothness function. It consists of two stages which are transformation and iteration process. In transformation stage, the errors obtained by any matching algorithm are transformed to possibility values according to these statistical distribution. Each grade of possility is updated by some constraints which are defined as smoothness, uniqueness, and discontinuity factor in iteration stage. The discontinuity factor is used to reserve discontinuity of disparity. In conventional methods, it is difficult to find proper weights and stop condition, because only two factors, smoothness and uniqueness, have been used. However, in the proposed mthod, the more smoothing is not ocurred because of discontinuity factor. And it is efective to the various image, even if the image has a severe noise and repeating patterns. In addition, it is shown that the convergence rate and the quality of output are improved.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.78-79
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• 1998

This paper describes a real time algorithm for blood flow estimation of LDF(laser Doppler flowmeter). Many algorithms for blood flow estimation are using power spectral density of Doppler signal by blood flow. In these research, the fast Fourier transformation is used to estimate power spectral density. This is a block processing procedure rather than real time processing. The algorithm in this paper used parametric spectral estimation. This has real time capability by estimation of AR(autoregressive) parameters sample by sample, and has smoothing power spectrum. Also, the frequency resolution is not limited by number of samples used to estimate AR parameter. Another advantage of this algorithm is that AR model enhance SNR.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.423-424
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• 2006

This paper proposes a hexahedral mesh generation scheme based on mapping approach and improves the drawback of sweeping algorithm. In order to improve the drawback, the algorithm in this paper generates hexahedral meshes by three dimensional element mapping first. Then hexahedral meshes are equivalent to geometry of the volume by mapping and smoothing. Sample meshes are constructed to demonstrate the mesh generating capability of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.984-990
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• 2002

We propose a new type of nonlinear fixed interval smoother to which an existing nonlinear smoother is modified. The nonlinear smoother is derived from two-filter formulas. For the backward filter. the propagation and the update equation of error states are derived. In particular, the modified update equation of the backward filter uses the estimated error terms from the forward filter. Data fusion algorithm, which combines the forward filter result and the backward filter result, is altered into the compatible form with the new type of the backward filter. The proposed algorithm is more efficient than the existing one because propagation in backward filter is very simple from the implementation point of view. We apply the proposed nonlinear smoothing algorithm to off-line navigation system and show the proposed algorithm estimates position, and altitude fairly well through the computer simulation.

• Korean Journal of Remote Sensing
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• v.3 no.1
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• pp.25-39
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• 1987

The purpose of this research is to develop the Automatic Fingerprint Verfication System by digital computer based on specially in PC level. Fingerprint is used as means of personal identity verification in view of that it has the high reliability and safety. Fingerprint pattern recognition algorithm is constitute of 3 stages, namely of the preprocessing, the feature extraction and the recognition. The preprocessing stage includes smoothing, binarization, thinning and restoration. The feature extraction stage includes the extraction of minutiae and its features. The recognition stage includes the registration and the matching score calculation which measures the similarity between two images. Tests for this study with 325 pairs of fingerprint resulted in 100% of separation which which in turn is turned out to be the reliability of this algorithm.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.10
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• pp.722-733
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• 2006

In scalable streaming application, there are two important knobs to tune to effectively exploit the underlying network resource and to maximize the user perceivable quality of service(QoS): layer selection and packet scheduling. In this work, we propose Semantics Aware Packet Scheduling (SAPS) algorithm to address these issues. Using packet dependency graph, SAPS algorithm selects a layer to maximize QoS. We aim at minimizing distortion in selecting layers. In inter-frame coded video streaming, minimizing packet loss does not imply maximizing QoS. In determining the packet transmission schedule, we exploit the fact that significance of each packet loss is different dependent upon its frame type and the position within group of picture(GOP). In SAPS algorithm, each packet is assigned a weight called QoS Impact Factor Transmission schedule is derived based upon weighted smoothing. In simulation experiment, we observed that QOS actually improves when packet loss becomes worse. The simulation results show that the SAPS not only maximizes user perceivable QoS but also minimizes resource requirements.

• The Korean Journal of Applied Statistics
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• v.32 no.6
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• pp.851-865
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• 2019

Discovering various features from one time series is complicated. In this paper, we introduce a multi aggregation prediction algorithm (MAPA) that uses the concepts of temporal aggregation and combining forecasts to find multiple patterns from one time series and increase forecasting accuracy. Temporal aggregation produces multiple time series and each series has separate properties. We use exponential smoothing methods in the next step to extract various features of time series components in order to forecast time series components for each series. In the final step, we blend predictions of the same kind of components and forecast the target series by the summation of blended predictions. As an empirical example, we forecast traffic accident counts using MAPA and observe that MAPA performance is superior to conventional methods.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.3
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• pp.120-127
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• 1998

In this paper, ultrasonic images of 25MHz bandwidth were acquired by applying peak value variation, time average and depth profile algorithm to acoustic microscopy and its performance was compared and analysed with each other. In the time average algorithm, total reflecting pulse wave from a spot on the coin was converted to digital data in time domain and average value of the converted 512 data was calculated in computer. Time average image was displayed by gray levels colour of acquired N x N matrix average data in the scanning area on the sample. This technique having smoothing effects in time domain make developed an ultrasonic image on a highly scattering area. In depth profile technique, time difference between the reference and the reflected signal was detected with minimum resolution performance of 2ns, thus we can acquired real 3 dimensional shape of the scanning area in accordance with relative magnitude. Through these experiments, peak value, time average and depth profile images were analysed and advantages of each algorithm were proposed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.6
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• pp.909-921
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• 1995

The objective of this paper is to develop an algorithm for a real-time automatic fingerprint recognition system. The algorithm employs the Fast Fourier Transform (FFT) in determining the directions of ridges in fingerprint images, and utilizes statistical information in recognizing the fingerprints. The information used in fingerprint recognition is based on the dircetions along ridge curves and characteristic points such as core points and delta points. In order to find ridge directions, the algorithm applies the FFT to a small block of the size 8x8 pixels, and decides the directions by interpreting the resulted Fourier spectrum. By using the FFT, the algorithm does not require conventional preprocessing procedures such as smoothing, binarization, thinning, and restorationl. Finally, in matching two fingerprint images, the algorithm searches and compares two kinds of feature blocks, one as the blocks where the dircetions cannot be defined from the Fourier spectrum, and the other as the blocks where the changes of directions become abrupt. The proposed algorithm has been implemented on a SunSparc-2 workstation under the Open Window environment. In the experiment, the proposed algorithm has been applied to a set of fingerprint images obtained by a prism system. The result has shown that while the rate of Type II error - Incorrect recognition of two different fingerprints as the identical fingerprints - is held at 0.0%, the rate of Type I error - Incorrect recognition of two identical fingerprints as the different ones - is 2.2%.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.12
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• pp.1062-1070
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• 2015

This paper presents an application of an optimal smoothing filter for moving target tracking problem based on measured noise source. In order to measure distance and velocity for the moving target, a beamforming method is applied to use the noise source by using microphone array. Also a Kalman filter and an optimal smoothing algorithm are adopted to improve accuracy of trajectory estimation by using a Singer target model. The simulation is conducted with a missile dynamics to verify performance of the optimal smoothing filter, and a model rocket is used for experiment environment to compare the trajectory estimation results between the beamforming, the Kalman filter, and the smoother. The Kalman filter results show better tracking performance than the beamforming technique, and the estimation results of the optimal smoother outperform the Kalman filter in terms of trajectory accuracy in the experiment results.