• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.5 no.4
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• pp.30-39
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• 1994

The resonant frequency, reflection cofficient and input impedance of a microstrip transverse dipole coupled electromagnetically are calculated using Finite Difference Time Domain(FDTD) method, and the evolution of gaussian pulse and spatial distribution of electromagnetic field components in the computation domain is represented graphically. Also, we confirmed the computation results show good agreement with the results of Method of Moment(MOM) and experiment[8] reported in the literature.

• Korean Journal of Remote Sensing
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• v.31 no.1
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• pp.21-28
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• 2015

The essential idea of de-noising is referring to neighboring pixels of a center pixel to be updated. Conventional adaptive de-noising filters use local statistics, i.e., mean and variance, of neighboring pixels including the center pixel. The drawback of adaptive de-noising filters is that their performance becomes low when edges are contained in neighboring pixels, while anisotropic diffusion de-noising filters remove adaptively noises and preserve edges considering intensity difference between neighboring pixel and the center pixel. The anisotropic diffusion de-noising filters, however, use only intensity difference between neighboring pixels and the center pixel, i.e., local statistics of neighboring pixels and the center pixel are not considered. We propose a new connectivity function of two adjacent pixels using statistics of neighboring pixels and apply connectivity function to diffusion coefficient. Experimental results using an aerial image corrupted by uniform and Gaussian noises showed that the proposed algorithm removed more efficiently noises than conventional diffusion filter and median filter.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1935-1939
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• 2006

In this study, the new dispersion-correction terms are added to leap-frog finite difference scheme for the linear shallow-water equations with the purpose of considering the dispersion effects such as linear Boussinesq equations for the propagation of tsunamis. And, dispersion-correction factor is determined to mimic the frequency dispersion of the linear Boussinesq equations. The numerical model developed in this study is tested to the problem that initial free surface displacement is a Gaussian hump over a constant water depth, and the results from the numerical model are compared with analytical solutions. The results by present numerical model are accurate in comparison with the past models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.710-726
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• 2018

This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.

• Journal of the Earthquake Engineering Society of Korea
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• v.23 no.1
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• pp.55-70
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• 2019

The phase properties of ground acceleration records from Mw 5.5~6.5 earthquakes are analyzed. The interrelationships between phase properties and significant durations, as well as PGA, are clarified through both of theoretical and empirical approaches. The probabilistic characteristics of phase information is also discussed based on previous studies and it is shown that circular normal distribution is the most appropriate probability distribution for the phase angle and phase difference. Whereas those variates can be modeled by Gaussian random variables. From the survey results on the frequency dependency of the phase statistics, a simple model is introduced, which is possible to express the frequency dependency of phase information. It is also shown that the significant duration can be controlled by appropriately chosen standard deviation of phase difference for 4~8Hz frequency band and additional consideration of phase scattering in higher frequency band through a series of Monte Carlo simulations. The source of phase scattering effect is also pointed out and discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1696-1705
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• 1996

The theory of stack filtering, which is a generalization of median filtering, is used to the detection of intensity edges in noisey images. The proposed approach, called the Difference of Estimates(DoE) approach, is a new formulation of a morphological scheme which has been very sensitive to impulse noise. In this approach, stack filters are applied to a noisy image to obtain local estimates of the dilated and eroded versions of the noise-free image. Thresholding the difference between these two estimates yields the binary edge map. We find that this approach yields results comparable to those obtained with the Canny operator for images with additive Gaussian noise, burt works much better when the noise is impulsive.

• Journal of the Optical Society of Korea
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• v.18 no.4
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• pp.317-329
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• 2014

In vision measurement systems based on structured light, the key point of detection precision is to determine accurately the central position of the projected laser line in the image. The purpose of this research is to extract laser line centers based on a decision function generated to distinguish the real centers from candidate points with a high recognition rate. First, preprocessing of an image adopting a difference image method is conducted to realize image segmentation of the laser line. Second, the feature points in an integral pixel level are selected as the initiating light line centers by the eigenvalues of the Hessian matrix. Third, according to the light intensity distribution of a laser line obeying a Gaussian distribution in transverse section and a constant distribution in longitudinal section, a normalized model of Hessian matrix eigenvalues for the candidate centers of the laser line is presented to balance reasonably the two eigenvalues that indicate the variation tendencies of the second-order partial derivatives of the Gaussian function and constant function, respectively. The proposed model integrates a Gaussian recognition function and a sinusoidal recognition function. The Gaussian recognition function estimates the characteristic that one eigenvalue approaches zero, and enhances the sensitivity of the decision function to that characteristic, which corresponds to the longitudinal direction of the laser line. The sinusoidal recognition function evaluates the feature that the other eigenvalue is negative with a large absolute value, making the decision function more sensitive to that feature, which is related to the transverse direction of the laser line. In the proposed model the decision function is weighted for higher values to the real centers synthetically, considering the properties in the longitudinal and transverse directions of the laser line. Moreover, this method provides a decision value from 0 to 1 for arbitrary candidate centers, which yields a normalized measure for different laser lines in different images. The normalized results of pixels close to 1 are determined to be the real centers by progressive scanning of the image columns. Finally, the zero point of a second-order Taylor expansion in the eigenvector's direction is employed to refine further the extraction results of the central points at the subpixel level. The experimental results show that the method based on this normalization model accurately extracts the coordinates of laser line centers and obtains a higher recognition rate in two group experiments.

• ETRI Journal
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• v.33 no.4
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• pp.528-536
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• 2011

In this paper, we analyze the location accuracy of real-time locating systems (RTLSs) in multipath environments in which the RTLSs comply with the ISO/IEC 24730-2 international standard. To analyze the location error of RTLS in multipath environments, we consider a direct path and indirect path, in which time and phase are delayed, and also white Gaussian noise is added. The location error depends strongly on both the noise level and phase difference under a low signal-to-noise ratio (SNR) regime, but only on the noise level under a high SNR regime. The phase difference effect can be minimized by matching it to the time delay difference at a ratio of 180 degrees per 1 chip time delay (Tc). At a relatively high SNR of 10 dB, a location error of less than 3 m is expected at any phase and time delay value of an indirect signal. At a low SNR regime, the location error range increases to 8.1 m at a 0.5 Tc, and to 7.3 m at a 1.5 Tc. However, if the correlation energy is accumulated for an 8-bit period, the location error can be reduced to 3.9 m and 2.5 m, respectively.

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.559-573
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• 2018

Recently, one of the most actively applied image media in the most fields such as virtual reality (VR) is omni-directional or panorama image. This image is generated by stitching images obtained by various methods. In this process, it takes the most time to extract keypoints necessary for stitching. In this paper, we analyze the parameters involved in the extraction of SIFT keypoints with the aim of reducing the computation time for extracting the most widely used SIFT keypoints. The parameters considered in this paper are the initial standard deviation of the Gaussian kernel used for Gaussian filtering, the number of gaussian difference image sets for extracting local extrema, and the number of octaves. As the SIFT algorithm, the Lowe scheme, the originally proposed one, and the Hess scheme which is a convolution cascade scheme, are considered. First, the effect of each parameter value on the computation time is analyzed, and the effect of each parameter on the stitching performance is analyzed by performing actual stitching experiments. Finally, based on the results of the two analyses, we extract parameter value set that minimize computation time without degrading.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.10
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• pp.54-63
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• 2007

To measure water levels from remote cites using a narrowband channel, this paper developed a difference image based JPEG communication scheme and a water level measurement scheme using the sparsely sampled images in time domain. In the slave system located in the field, the images are compressed using JPEG after changed to difference images, among which in a period of data collection those showing larger changes are sampled and transmitted. To measure the water level from the images received in the master system which may contain noises caused by various sources, the averaging scheme and Gaussian filter are used to reduce the noise effects and the Y axis profile of an edge image is used to read the water level. Considering the wild condition of the field, a simplified camera calibration scheme is also introduced. The implemented slave system was installed at a river and its performance has been tested with the data collected for a month.