• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.959-967
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• 2004

Jain et al. proposed the hybrid matching method which was combined the minutia-based matching method and the filter-bank based matching method. And, their experimental results proved the hybrid matching method was more effective than each of them. However, this hybrid method cannot utilize each peculiar advantage of two methods. The reason is that it gets the matching score by simply summing up each weighted matching score after executing two methods individually. In this paper, we propose new hybrid matching method. It mixes two matching methods during the feature extraction process. This new hybrid method has lower ERR than the filter-bank based method and higher ERR than the minutia-based method. So, we propose the adaptive hybrid scoring method, which selects the matching score in order to preserve the characteristics of two matching methods. Using this method, we can get lower ERR than the hybrid matcher by Jain et al. Experimental results indicate that the proposed methods can improve the matching performance up to about 1% in ERR.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.4
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• pp.474-480
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• 2020

With the advent of the Fourth Industrial Revolution, many new technologies are being utilized. In particular, video signals are used in various fields. However, when transmitting and receiving video signals, salt and pepper noise and additive white Gaussian noise (AWGN) occur for multiple reasons. Failure to remove such noise when performing image processing can cause problems. Generally, filters such as CWMF, MF, and AMF remove noise. However, these filters perform somewhat poorly in the high-density noise domain and cause smoothing, resulting in slightly lower retention of the edge components. In this paper, we propose an algorithm by effectively eliminating salt and pepper noise using a modified weight filter using standard deviation. In order to prove the noise reduction performance of the proposed algorithm, we compared it with the existing algorithm using PSNR and magnified images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.213-215
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• 2021

With the development of IoT technology, various technologies such as artificial intelligence and automation are being grafted into industrial sites, and accordingly, the importance of data processing is increasing. In particular, a system based on a digital image may cause a malfunction due to noise in the image due to a sensor defect or a communication environment problem. Therefore, research on image processing has been continued as a pre-processing process, and an effective noise reduction technique is required depending on the type of noise and the characteristics of the image. In this paper, we propose a modified spatial weight filter to protect edge components in the impulse noise reduction process. The proposed algorithm divides the filtering mask into four regions and calculates the standard deviation of each region. The final output was filtered by applying a spatial weight to the region with the lowest standard deviation value. Simulation was conducted to evaluate the performance of the proposed algorithm, and it showed superior impulse noise reduction performance compared to the existing method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2679-2691
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• 2012

In this paper, a high accuracy stereo reconstruction method for surgery instruments positioning is proposed. Usually, the problem of surgical instruments reconstruction is considered as a basic task in computer vision to estimate the 3-D position of each marker on a surgery instrument from three pairs of image points. However, the existing methods considered the 3-D reconstruction of the points separately thus ignore the structure information. Meanwhile, the errors from light variation, imaging noise and quantization still affect the reconstruction accuracy. This paper proposes a method which takes the structure information of surgical instruments as constraints, and reconstructs the whole markers on one surgical instrument together. Firstly, we calibrate the instruments before navigation to get the structure parameters. The structure parameters consist of markers' number, distances between each markers and a linearity sign of each instrument. Then, the structure constraints are added to stereo reconstruction. Finally, weighted filter is used to reduce the jitter. Experiments conducted on surgery navigation system showed that our method not only improve accuracy effectively but also reduce the jitter of surgical instrument greatly.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.389-392
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• 2000

본 연구에서는 1, 2단자쌍 회로망의 임피던스 정합회로를 간단하고 빠르게 구할 수 있는 방안을 개발하였다. 우선 회로망의 전체 전달함수를 F 행열로 부터 계산하고, 이를 이용하여 양단의 부하저항 및 정합회로가 포함된 각각의 단자의 입출력 임피던스를 구하였으며, 이 식으로부터 정합용 소자의 정확한 값을 계산하였다. 본 연구의 타당성을 검증하기 위해 CDMA용 소자로 널리 사용되는 중간주파수 대역 withdrawal 가중형 SAW 필터에 본 연구의 결과를 적용하여 임피던스 정합 전후의 특성변화를 시뮬레이션과 실험을 통하여 동시에 확인하였다 그 결과 85.38 MHz의 중심주파수에서 비대역폭이 $1.2\%$, 삽입손실이 29dB, VSWR이 80인 필터를 본 연구방법을 이용하여 정합 한 경우, 각각 $1.8\%$, 9dB, 3으로 향상됨을 시뮬레이션과 실험을 통해 확인하였다. 본 연구결과는 SAW 디바이스의 정합에 매우 용이하게 이용될 수 있을 뿐만 아니라 일반적인 1, 2단자쌍 회로망의 임피던스 정합에도 널리 사용될 수 있다

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1166-1179
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• 2013

In wireless sensor network (WSN) environments, environmental noises are generated by, for example, small passing animals, crickets chirping or foliage blowing and will interfere target detection if the noises are higher than the sensor threshold value. For accurate tracking by acoustic WSNs, these environmental noises should be filtered out before initiating track. This paper presents the effect of environmental noises on target tracking and proposes a new algorithm for the noise mitigation in acoustic WSNs. We find that our noise mitigation algorithm works well even for targets with sensing range shorter than the sensor separation as well as with longer sensing ranges. It is also found that noise duration at each sensor affects the performance of the algorithm. A detection algorithm is also presented to account for the Doppler effect which is an important consideration for tracking higher-speed ground targets. For tracking, we use the weighted sensor position centroid to represent the target position measurement and use the Kalman filter (KF) for tracking.

• Smart Structures and Systems
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• v.22 no.3
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• pp.315-326
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• 2018

This paper presents a novel time-domain method for the identification of plastic rotations and stiffness parameters of single-bay frames with nonlinear plastic hinges. Each plastic hinge is modelled as a pseudo-semi-rigid connection with nonlinear hysteretic moment-curvature characteristics at an element end. Through the comparison of the identified end rotations of members that are connected together, the plastic rotation that furnishes information of the locations and plasticity degrees of plastic hinges can be identified. The force consideration of the frame members may be used to relate the stiffness parameters to the elastic rotations and the excitation. The damped-least-squares method and damped-and-weighted-least-squares method are adopted to estimate the stiffness parameters of frames. A noise-removal strategy employing a de-noising technique based on wavelet packets with a smoothing process is used to filter out the noise for the parameter estimation. The numerical examples show that the proposed method can identify the plastic rotations and the stiffness parameters using measurements with reasonable level of noise. The unknown excitation can also be estimated with acceptable accuracy. The advantages and disadvantages of both parameter estimation methods are discussed.

• Journal of Advanced Navigation Technology
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• v.16 no.4
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• pp.593-601
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• 2012

This paper develops and analyzes a new multiple-hypothesis Receiver Autonomous Integrity Monitoring (RAIM) algorithm as a candidate for future standard architecture. The proposed algorithm can handle simultaneous multiple failures as well as a single failure. It uses measurement residuals and satellite observation matrices of several consecutive epochs for Failure Detection and Exclusion (FDE). The proposed algorithm redueces the Minimum Detectable Bias (MDB) via the Relative RAIM (RRAIM) scheme. Simulation results show that the proposed algorithm can detect and filter out multiple failures in tens of meters.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.68-68
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• 2017

Measurements of solar wind speed near the Sun (< 0.1 AU) are important for understanding acceleration mechanism of solar wind as well as space weather predictions, but hard to directly measure them. For the first time, we provide 2D solar wind speed maps in the LASCO field of view using three consecutive days data. By applying the Fourier convolution and inverse Fourier transform, we decompose the 3D intensity data (r, PA, t) into the 4D one (r, PA, t, v). Then, we take the weighted mean along speed to determine the solar wind speeds that gives V(r, PA, t) in every 30 min. The estimated radial speeds are consistent with those given by an artificial flow and plasma blobs. We find that the estimated speeds are moderately correlated with those from slow CMEs and those from IPS observations. A comparison of yearly solar wind speed maps in 2000 and 2009 shows that they have very remarkable differences: azimuthally uniform distribution in 2000 and bi-modal distribution (high speed near the poles and low speed near the equator) in 2009.

• Journal of Satellite, Information and Communications
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• v.8 no.1
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• pp.77-82
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• 2013

The object tracking method using particle filtering has been proved successful since it is based on the Monte Carlo simulation to estimate the posterior distribution of the state vector that is nonlinear and non-Gaussian in the real-world situation. In this paper, we present two nobel methods that can improve the performance of the object tracking algorithm based on the particle filtering. First one is the feedback method that replace the low-weighted tracking sample by the estimated state vector in the previous frame. The second one is an tracking box correction method to find an confidence interval of back projection probability on the estimated candidate object area. An sample propagation equation is also presented, which is obtained by experiments. We designed well-organized test data set which reflects various challenging circumstances, and, by using it, experimental results proved that the proposed methods improves the traditional particle filter based object tracking method.