• Journal of Korea Multimedia Society
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• v.3 no.6
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• pp.592-603
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• 2000

This paper is concerning off-line signature verification using a density function which is obtained by convolving the signature image with twelve-directional $5\times{5}$ gradient masks and the weighted fuzzy mean classifier. The twelve-directional density function based on Nevatia-Babu template gradient is related to the overall shape of a signature image and thus, utilized as a feature set. The weighted fuzzy mean classifier with the reference feature vectors extracted from only genuine signature samples is evaluated for the verification of freehand forgeries. The experimental results show that the proposed system can classify a signature whether it is genuine or forged with more than 98% overall accuracy even without any knowledge of varied freehand forgeries.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.343-347
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• 2012

Non-linear equalization techniques using decision feedback structure are highly demanded for cancellation of intersymbol interferences occurred in severe channel environments. In this paper decision feedback structure is applied to the linear blind equalizer algorithm that is based on information theoretic learning and a randomly generated symbol set. At the decision feedback equalizer (DFE) the random symbols are generated to have the same probability density function (PDF) as that of the transmitted symbols. By minimizing difference between the PDF of blind DFE output and that of randomly generated symbols, the proposed DFE algorithm produces equalized output signal. From the simulation results, the proposed method has shown enhanced convergence and error performance compared to its linear counterpart.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.75-88
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• 2008

This paper presents a spatial-level nonparametric multi-focus image fusion technique based on kernel estimates of input image blocks' underlying class-conditional probability density functions. Image fusion is approached as a classification task whose posterior class probabilities, P($wi{\mid}Bikl$), are calculated with likelihood density functions that are estimated from the training patterns. For each of the C input images Ii, the proposed method defines i classes wi and forms the fused image Z(k,l) from a decision map represented by a set of $P{\times}Q$ blocks Bikl whose features maximize the discriminant function based on the Bayesian decision principle. Performance of the proposed technique is evaluated in terms of RMSE and Mutual Information (MI) as the output quality measures. The width of the kernel functions, ${\sigma}$, were made to vary, and different kernels and block sizes were applied in performance evaluation. The proposed scheme is tested with C=2 and C=3 input images and results exhibited good performance.

• Investigative Magnetic Resonance Imaging
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• v.15 no.1
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• pp.57-66
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• 2011

Purpose : A new inhomogeneity correction method based on two-point Dixon sequence is proposed to obtain water and fat images at 0.35T, low field magnetic resonance imaging (MRI) system. Materials and Methods : Joint phase-magnitude density function (JPMF) is obtained from the in-phase and out-of-phase images by the two-point Dixon method. The range of the water signal is adjusted from the JPMF, and 3D inhomogeneity map is obtained from the phase of corresponding water volume. The 3D inhomogeneity map is used to correct the inhomogeneity field iteratively. Results : The proposed water-fat imaging method was successfully applied to various organs. The proposed 3D inhomogeneity correction algorithm provides good performances in overall multi-slice images. Conclusion : The proposed water-fat separation method using JPMF is robust to field inhomogeneity. Three dimensional inhomogeneity map and the iterative inhomogeneity correction algorithm improve water and fat imaging substantially.

• Journal of the Korea Computer Graphics Society
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• v.18 no.2
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• pp.9-15
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• 2012

In this paper, we propose a method to segment a color image into several meaningful regions. We suppose that the meaningful region has a set of colors with high frequency in the color image. To find these colors, the color image is represented as several sets of color points in RGB space. And when we use the density of points defined in this method, color belonging to a dense region of color points in RGB space refers to the color that appeared frequently in the image. Eventually, we can find meaningful regions by looking for regions with high density of color points using our level set function in RGB space. However, if a meaningful region does not have a contiguous region of the sufficient size in the image, this is not a meaningful region but meaningless region. Thus, the pixels in the meaningless region are assigned to the biggest meaningful region belonging to its neighboring pixels in the color image. Our method divides the color image into meaningful regions by applying the density of color points to level set function in RGB space. This is different from the existing level set method that is defined only in 2D image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.9A
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• pp.1459-1464
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• 2001

본 논문에서는 나카가미 페이딩에서 STTD(Space Time Transmitter Diversity)기법을 적용한 셀룰러 무선 시스템의 오수신확률을 유도한다. 라플라스 변환을 이용하여 L개의 독립적이고 동일분포의 다중간섭신호에 대한 새로운 확률밀도함수를 유도하고, 동일채널 나카가미 간섭신호속에서 나카가미 페이딩을 겪는 신호에 대한 오수신확률을 나타내며, 주파수 재사용거리의 함수로 오수신확률을 표현한다.

• Journal of IKEEE
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• v.15 no.3
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• pp.198-204
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• 2011

In this letter, another analytical approach for the opportunistic amplify-and-forward (OAF) relay systems is proposed over Rayleigh fading channels. Based on set-operation at the selected relay node, its selection probability as the best relay is derived and then, the probability density function (PDF) of the received instantaneous signal-to-noise ratio (SNR) is expressed as a more tractable form in which the number of summations and the length of each summation are specified. Then, the average error rate, outage probability, and average channel capacity are obtained as approximated closed-forms. Simulation results are finally presented to validate that the proposed analytical expressions can be a unified frame work covering all Rayleigh fading channel conditions. Furthermore, it is confirmed that OAF schemes can outperform the other non-selective schemes on the average error rate, outage probability, and average channel capacity.

• Journal of the Earthquake Engineering Society of Korea
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• v.5 no.1
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• pp.73-80
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• 2001

구조물이 가지는 에너지의 확률밀도함수를 이용한 능도제어 알고리듬을 제안한다. 구조물의 에너지는 Rayleigh 확률분포를 가지는 것으로 가정된다. 이것은 에너지가 항상 양의 값을 가지고 최소에너지가 발생할 확률은 1이라는 조건을 Rayleigh 확률분포가 만족시킨다는 사실에 근거한다. 제어력의 크기는 가정된 확률밀도함수에 따라 구조물의 에너지가 설계자에 의해 설정된 에너지 임계값을 넘을 확률의 크기에 비례하도록 산정되며, 제어력의 방향은 Lyapunov 제어기 설계기법에 따라 결정된다. 제시된 알고리듬은 LQR 제어기와 비교하여 최대응답을 줄이는 효과를 가지며, 제어력의 임계를 고려할 수 있는 장점을 가진다. 또한 Lyapunov 제어기에서 발생가능한 채터링(chattering)현상을 피할 수 있다.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.891-904
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• 2006

The estimation of the probability precipitation is essential for the design of hydrologic projects. The techniques to calculate the probability precipitation can be determined by the point frequency analysis and the regional frequency analysis. The regional frequency analysis includes index-flood technique and L-moment technique. In the regional frequency analysis, even if the rainfall data passed homogeneity, suitable distributions can be different at each point. However, the regional frequency analysis can supplement the lacking precipitation data. Therefore, the regional frequency analysis has weaknesses compared to parametric point frequency analysis because of suppositions about probability distributions. Therefore, this paper applies kernel density function to precipitation data so that homogeneity is defined. In this paper, The data from 16 rainfall observatories were collected and managed by the Korea Meteorological Administration to achieve the point frequency analysis and the regional frequency analysis. The point frequency analysis applies parametric technique and nonparametric technique, and the regional frequency analysis applies index-flood techniques and L-moment techniques. Also, the probability precipitation was calculated by the regional frequency analysis using variable kernel density function.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.416-422
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• 2019

This paper proposes a GPU-based modeling and rendering of 3D clouds using procedural functions. The formation of clouds is based on modified noise function made with fbm(Fractional Brownian Motion). Those noise values turn into densities of droplets of liquid water, which is a critical parameter for forming the three different types of clouds. At the rendering stage, the algorithm applies the ray marching technique to decide the colors of cloud using density values obtained from the noise function. In this process, all lighting attenuation and scattering are calculated by physically based manner. Once we have the clouds, they are blended on the sky, which is also rendered physically. We also make the clouds moving in the sky by the wind force. All algorithms are implemented and tested on GPU using GLSL.