• Journal of Environmental Health Sciences
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• v.34 no.2
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• pp.148-152
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• 2008

Coated filters were developed to replace the glass impinger methods that use reagent solutions. The purpose of this study was to simultaneously measure nitrogen dioxide ($NO_2$) and respirable suspended particles (RSP) by a filtration method with a cyclone connected to a pump. A first pre-filter for RSP and second filter for $NO_2$, which was soaked in a TEA (Triethanolamine) solution, were loaded into a filter cassette with a pump flow rate of 1.7 l/m. After sampling, the TEA soaked filter was removed from the cassette, placed in a large test tube (10 ml), mixed, and allowed time to develop. The absorbance (abs) of the diazo compound of the $NO_2$ and N-(1-Napthylethylenediamine dihydrochloride) in the color reagent was measured at 545 nm on a spectrophotometer. The collection efficiency(%) of $NO_2$ by each 3 filter soaked in TEA solution and used in the cyclone with a pump flow rate 1.7 l/m was $89{\pm}3%$ and the correlation coefficient between the true $NO_2$ concentration and that determined by the TEA soaked filters was 0.993(p<0.001).

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.1
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• pp.132-144
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• 1997

The rotation-invariant pattern recognition filter using circular harmonic function of the wavelet transforme dsreference image by morlet, mexican-hat, and haar wavelt function is proposed. The rotated reference images, the images sililar to the reference image, and the images which are added by random noise are used for the inpt images, and in case of the input images with random noise, they are applied to the recognition after removing the random noise by the transformed moving average method with proper thresholding value and window size. The proposed optical wavelet circular harmonic matched filter (WCHMF) is a type of the matche dfilter, so that it can be applied to the 4f vander lugt optical correlation system. SNR and discrimination capability of the proposed filter are compared with those of the conventional HF, the POCHF, and the BPOCHF. The proper wavelet function for the reference image used in this paper is achieved by applying morlet, mexican-hat, and harr wavelet function ot the proposed filter, and the proposed filter has good SNR and discrimination capability with rotation-invariance in case of the morlet wavelet function.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.568-574
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• 2002

The main issue of noise reduction of image is how to preserve edge and reduce noise. Usually, The Wiener falter is used for this purpose. But the conventional Wiener filter cannot remove noise well in both edge and smooth region due to the single size estimation window. In addition, it ignores the correlation between pixels. In this paper, we propose a new noise reduction algorithm, in which adaptive estimation window is used according to property of smooth region and edge region. In order to make edge more clear, directional Gaussian mask and directional estimation window combines to the Wiener filter according to direction of edge. From the simulation results, it can be seen that the proposed algorithm showed improves performance in both PSNR arid subjective evaluation

• Journal of the Korean Society of Tobacco Science
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• v.23 no.2
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• pp.179-184
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• 2001

This study was conducted to determine the smoke component distribution and the relationship between chemical components and physical characteristics of cigarettes. 16 different cigarette brands which were sold in the market were selected for this study. Five kinds of smoke components which have been tar, nicotine, water, carbon monoxide(CO) puff No., and six kinds of physical characteristics which were filter type, leaf weight, filter weight, UPD, EPD, dilution rate were analyzed. The average values in tar, nicotine, water, CO concentration were 6.5 mg/cig. 0.66 mg/cig, 1.12 mg/cig. and 6.32 mg/cig., respectively. The average ratios of nicotine/tar and CO/tar were 0.10, and 1.02 respectively. The distribution of smoke components collected in the cambridge filter and cigarette filter was different. The averages of tar and nicotine removal efficiency by a cigarette filter were 53%, and 48%, respectively. All smoking components were positively correlated with other smoking components. filter types, EPD, and dilution rate were showed high correlation to the changes of smoke components. Especially, dilution rate of cigarette strongly affected on the changes of all smoke components.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.425-428
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• 1999

The radar interferogram represents phase differences between the two synthetic aperture radar observations acquired in slightly different angle. The success of the radar interferometric application largely depends on the quality of the interferogram generated from two or more synthetic aperture radar data sets. We propose here to apply the wavenumber correlation analysis to the in-phase and quadrature phase of the radar interferogram. The wavenumber correlation analysis is to resolve the highly correlated components from the low correlation components by estimating correlation coefficients for each wavenumber component. Through this approach, one can easily distinguish the signal components from the noise components in the wavenumber domain. Therefore, the wavenumber correlation analysis of the radar interferogram can be utilized to design post filter and to estimate the quality of interferogram. We have tested the wavenumber correlation analysis using a Radarsat SAR data pair to demonstrated the effectiveness of

• International Journal of Contents
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• v.3 no.2
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• pp.35-39
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• 2007

The cognitive radio communication is taking the attentions because the development of the technique came to be possible to analyze wireless signals. In the IEEE 802.22 WRAN Systems[1], how to detect a spectrum and signals is continuously studied. In this paper, we propose the efficient signal detection method using SCF (Spectral Correlation Function). It is easy to detect the signal feature when we are using the SCF. Because most modulated signals have the cyclo-stationarity which is unique for each signal. But the fading channel effected serious influence even though it detects the feature of the signal. We applied LMS(Least Mean Square) filter for the compensation of the signal which is effected the serious influence in the fading channel. And we analyze some signal patterns through the SCF. And we show the unique signal feature of each signal through the SCF method. It is robust for low SNR(Signal to Noise Ratio) environment and we can distinguish it in the fading channel using LMS Filter.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.98.5-98
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• 2001

An efficient adaptive nonlinear compensator, based on a wavelet transform domain adaptive Volterra filter along with a modified escalator algorithm, is proposed to speed up the convergence rate of an adaptive LMS algorithm. In particular, it is well known that the e.g., slow convergence speed of an adaptive LMS algorithm depends on the statistical characteristics (e.g., large eigenvalue spread) of the corresponding auto-correlation matrix of the input vector. To solve such a convergence problem, the proposed approach utilizes a modified escalator algorithm and a wavelet transform domain adaptive LMS Volterra filtering technique, which leads to diagonalization of the auto-correlation matrix of the ...

• 한국가시화정보학회:학술대회논문집
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• 2002.11a
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• pp.7-10
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• 2002

A novel two-phase PIV algorithm using a single camera has been proposed, which introduces a method of image-separation into respective phase images, and is applied to freely rising single bubble. Gas bubble, tracer particle and background each have different gray intensity ranges on the same image frame when reflection and dispersion in the phase interface are intrinsically eliminated by optical filters and fluorescent material. Further, the signals of the two phases do not interfere with each other. Gas phase velocities are obtained from the separated bubble image by applying the two-frame PTV. On the other hand, liquid phase velocities are obtained from the tracer particle image by applying the cross-correlation algorithm. Moreover, in order to increase the SNR (signal-to-noise ratio) of the cross-correlation of tracer particle image, image enhancement is employed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4929-4947
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• 2017

In visual object tracking, Correlation Filter-based Tracking (CFT) systems have arouse recently to be the most accurate and efficient methods. The CFT's circularly shifts the larger search window to find most likely position of the target. The need of larger search window to cover both background and object make an algorithm sensitive to the background and the target occlusions. Further, the use of fixed-sized windows for training makes them incapable to handle scale variations during tracking. To address these problems, we propose two layer target representation in which both global and local appearances of the target is considered. Multiple local patches in the local layer provide robustness to the background changes and the target occlusion. The target representation is enhanced by employing additional reversed RGB channels to prevent the loss of black objects in background during tracking. The final target position is obtained by the adaptive weighted average of confidence maps from global and local layers. Furthermore, the target scale variation in tracking is handled by the statistical model, which is governed by adaptive constraints to ensure reliability and accuracy in scale estimation. The proposed structural enhancement is tested on VTBv1.0 benchmark for its accuracy and robustness.

• Journal of Broadcast Engineering
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• v.24 no.7
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• pp.1266-1275
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• 2019

With increasing criminal rates and number of CCTVs, much attention has been paid to intelligent surveillance system on the horizon. Object detection and tracking algorithms have been developed to reduce false alarms and accurately help security agents immediately response to undesirable changes in video clips such as crimes and accidents. Many studies have proposed a variety of algorithms to improve accuracy of detecting and tracking objects outside tunnels. The proposed methods might not work well in a tunnel because of low illuminance significantly susceptible to tail and warning lights of driving vehicles. The detection performance has rarely been tested against the tunnel environment. This study investigated a feasibility of object detection and tracking in an actual tunnel environment by utilizing YOLOv3 and Kernelized Correlation Filter. We tested 40 actual video clips to differentiate pedestrians and motorcycles to evaluate the performance of our algorithm. The experimental results showed significant difference in detection between pedestrians and motorcycles without false positive rates. Our findings are expected to provide a stepping stone of developing efficient detection algorithms suitable for tunnel environment and encouraging other researchers to glean reliable tracking data for smarter and safer City.