• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.615-618
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• 2019

Visual saliency detection is an important part in various vision-based applications. There are a myriad of techniques for saliency detection in color images. However, the number of methods for saliency detection in infrared images is inadequate. In this paper, we introduce a simple approach for pedestrian identification in infrared images using saliency. The input image is thresholded into several Boolean maps, an initial saliency map is then calculated as a weighted sum of created Boolean maps. The initial map is further refined by using thresholding, morphology operation, and Gaussian filter to produce the final, high-quality saliency map. The experiment showed that the proposed method produced high performance results when applied to real-life data.

• Kyungpook Mathematical Journal
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• v.62 no.3
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• pp.497-507
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• 2022

In this study, we define tubular surfaces in Pseudo Galilean 3-space as type-1 or type-2. Using the X(s, t) position vectors of the surfaces and G(s, t) Gaussian transformations, we obtain equations for the two types of tubular surfaces that satisfy the conditions ∆X(s, t) = 0, ∆X(s, t) = AX(s, t), ∆X(s, t) = λX(s, t), ∆X(s, t) = ∆G(s, t), ∆G(s, t) = 0, ∆G(s, t) = AG(s, t) and ∆G(s, t) = λG(s, t).

• Journal of Korea Multimedia Society
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• v.9 no.3
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• pp.296-306
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• 2006

We proposed the algorithm for the quantization noise reduction based on variable filter adaptive to edge signal in MPEG postprocessing system. In our algorithm, edge map and local modulus maxima in the decoded images are obtained by using 2D Mallat wavelet tilter. And then, blocking artifacts in inter-block are reduced by Gaussian LPF that is variable to filtering region according to edge map. Ringing artifacts in intra-block are reduced by 2D SAF according to local modulus maxima. Experimental results show that the proposed algorithm was superior to the conventional algorithms as regards PSNR, which was improved by 0.04-0.20 dB, and the subjective image quality.

• Journal of Biomedical Engineering Research
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• v.32 no.3
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• pp.245-250
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• 2011

Parallel imaging technique can provide several advantages for a multitude of MRI applications. Especially, in SENSE technique, sensitivity maps were always required in order to determine the reconstruction matrix, therefore, a number of difference approaches using sensitivity information from coils have been demonstrated to improve of image quality. Moreover, many filtering methods were proposed such as adaptive matched filter and nonlinear diffusion technique to optimize the suppression of background noise and to improve of image quality. In this study, we performed SENSE reconstruction using computer simulations to confirm the most suitable method for the feasibility of filtering effect and according to changing order of polynomial fit that were applied on variation of spatial resolution of sensitivity map. The image was obtained at 0.32T(Magfinder II, Genpia, Korea) MRI system using spin-echo pulse sequence(TR/TE = 500/20 ms, FOV = 300 mm, matrix = $128{\times}128$, thickness = 8 mm). For the simulation, obtained image was multiplied with four linear-array coil sensitivities which were formed of 2D-gaussian distribution and the image was complex white gaussian noise was added. Image processing was separated to apply two methods which were polynomial fitting and filtering according to spatial resolution of sensitivity map and each coil image was subsampled corresponding to reduction factor(r-factor) of 2 and 4. The results were compared to mean value of geomety factor(g-factor) and artifact power(AP) according to r-factor 2 and 4. Our results were represented while changing of spatial resolution of sensitivity map and r-factor, polynomial fit methods were represented the better results compared with general filtering methods. Although our result had limitation of computer simulation study instead of applying to experiment and coil geometric array such as linear, our method may be useful for determination of optimal sensitivity map in a linear coil array.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.65-83
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• 2022

Although various statistical methods have been developed to map time-dependent genetic factors, most identified genetic variants can explain only a small portion of the estimated genetic variation in longitudinal traits. Gene-gene and gene-time/environment interactions are known to be important putative sources of the missing heritability. However, mapping epistatic gene-gene interactions is extremely difficult due to the very large parameter spaces for models containing such interactions. In this paper, we develop a Gaussian process (GP) based nonparametric Bayesian variable selection method for longitudinal data. It maps multiple genetic markers without restricting to pairwise interactions. Rather than modeling each main and interaction term explicitly, the GP model measures the importance of each marker, regardless of whether it is mostly due to a main effect or some interaction effect(s), via an unspecified function. To improve the flexibility of the GP model, we propose a novel grid-based method for the within-subject dependence structure. The proposed method can accurately approximate complex covariance structures. The dimension of the covariance matrix depends only on the number of fixed grid points although each subject may have different numbers of measurements at different time points. The deviance information criterion (DIC) and the Bayesian predictive information criterion (BPIC) are proposed for selecting an optimal number of grid points. To efficiently draw posterior samples, we combine a hybrid Monte Carlo method with a partially collapsed Gibbs (PCG) sampler. We apply the proposed GP model to a mouse dataset on age-related body weight.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.89-90
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• 2008

AWGN(Addictive white gaussian noise)에 의해 영상은 자주 훼손되곤 한다. 최근 이를 복원하기위해 웨이블릿(Wavelet) 영역에서의 베이시안(Bayesian) 추정법이 연구되고 있다. 웨이블릿 변환된 영상 신호의 밀도 함수(pdf)는 표족한 첨두와 긴 꼬리(long-tail)를 갖는 경망이 있다. 이러한 사전 밀도 함수(a priori probability density function)를 상황에 적합하게 추정한다면 좋은 성능의 복원 결과를 얻을 수 있다. 빈번이 제안되는 릴도 함수로 가우시안(Gaussian) 분포 참수와 라플라스(Laplace) 분포 함수가 있다. 이들 각각의 모델은 훌륭히 변환 계수들을 모델링하며 나름대로의 장점을 나타낸다. 본 연구에서는 가우시안 분포와 라플라스(Laplace) 분포의 혼합 분포 모델을 밀도 함수로 제안하여, 이 들의 장점을 종합하였다. 이를 MAP(Maximum a Posteriori) 추정 방법에 적용하여 잡음을 제거 하였다. 그 결과 기존의 알고리즘에 비해 시각적인 면(Visual aspect), 수치적인 면(PSNR), 그리고 연산량(Complexity) 측면에서 망상된 결과를 얻었다.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.88-93
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• 2020

Based on the capture-emission energy (CEE) maps of CMOS devices, a physics-informed machine learning model for the bias temperature instability (BTI)-induced threshold voltage shifts and low frequency noise is presented. In order to incorporate physics theories into the machine learning model, the integration of artificial neural network (IANN) is employed for the computation of the threshold voltage shifts and low frequency noise. The model combines the computational efficiency of IANN with the optimal estimation of Gaussian mixture model (GMM) with soft clustering. It enables full lifetime prediction of BTI under various stress and recovery conditions and provides accurate prediction of the dynamic behavior of the original measured data.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.5
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• pp.277-285
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• 2016

Moving object detection system has been an emerging research field in various advanced driver assistance systems (ADAS) and surveillance system. In this paper, we propose two optical flow based moving object detection methods at dynamic scenes. Both proposed methods consist of three successive steps; pre-processing, foreground segmentation, and post-processing steps. Two proposed methods have the same pre-processing and post-processing steps, but different foreground segmentation step. Pre-processing calculates mainly optical flow map of which each pixel has the amplitude of motion vector. Dense optical flows are estimated by using Farneback technique, and the amplitude of the motion normalized into the range from 0 to 255 is assigned to each pixel of optical flow map. In the foreground segmentation step, moving object and background are classified by using the optical flow map. Here, we proposed two algorithms. One is Gaussian mixture model (GMM) based background subtraction, which is applied on optical map. Another is adaptive thresholding based foreground segmentation, which classifies each pixel into object and background by updating threshold value column by column. Through the simulations, we show that both optical flow based methods can achieve good enough object detection performances in dynamic scenes.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.60.2-60.2
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• 2018

We present the near infrared JHK photometric properties and the spatial distribution of red supergiants(RSGs) of NGC 3623, NGC 3627 and NGC 3628 in the Leo Triplet system using the data obtained with 3.8m UKIRT(United Kingdom Infra-Red Telescope) at Hawaii. We checked interaction between the three galaxies by making a spatial density map of RSGs. From (J-K,K)0 Color-Magnitude Diagram which include resolved stars in three galaxy and control field with PARSEC isochrone, we figured out the RSG candidates of the Leo triplet are at 0.9<(J-K)0<1.2, mK<17.5 and separated them from background and foreground sources. Using gaussian kernel density estimation, we drew spatial density map of RSGs in the Leo triplet with an assumption that all RSGs are an identical population. The density map shows extended features of NGC 3628 to NGC 3627 along the declination direction. The asymmetries between NGC 3627 and NGC 3628 might be evidence for that the distribution of actual star components(RSGs) follows the neutral hydrogen distribution and also for interaction between two galaxies. And the extended features along the right ascension direction might be a supporting evidence for the existence of a TDG(Tidal Dwarf Galaxy). In case of NGC 3623, we could not see any sign of interaction in density map.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.286-289
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• 2012

본 논문은 3차원 깊이 정보를 이용하여 감시카메라에서 움직이는 사람을 검출하고 추적하는 방법을 제안한다. 제안하는 방법은 GMM(Gaussian mixture model)을 이용하여 배경과 움직이는 사람을 분리한 후, 분리된 영역을 CCL(connected-component labeling)을 통하여 각각 블랍(blob) 단위로 나누고 그 블랍을 추적한다. 그 중 블랍 단위로 나누는 데 있어 두 블랍이 합쳐진 경우, 3차원 깊이 정보를 이용하여 두 블랍을 분리하는 방법을 제안한다. 실험을 통하여 제안하는 방법의 결과를 보인다.