• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2118-2125
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• 2014

Gait Recognition is a new technique to identify the people by the way they walk. Human gait is a spatio-temporal phenomenon that typifies the motion characteristics of an individual. The proposed method makes a simple but efficient attempt to gait recognition. For each video file, spatial silhouettes of a walker are extracted by an improved background subtraction procedure using Gaussian Mixture Model (GMM). Here GMM is used as a parametric probability density function represented as a weighted sum of Gaussian component densities. Then, the relevant features are extracted from the silhouette tracked from the given video file using the Principal Component Analysis (PCA) method. The Fisher Linear Discriminant Analysis (FLDA) classifier is used in the classification of dimensional reduced image derived by the PCA method for gait recognition. Although gait images can be easily acquired, the gait recognition is affected by clothes, shoes, carrying status and specific physical condition of an individual. To overcome this problem, it is combined with footprint as a multimodal biometric system. The minutiae is extracted from the footprint and then fused with silhouette image using the Discrete Stationary Wavelet Transform (DSWT). The experimental result shows that the efficiency of proposed fusion algorithm works well and attains better result while comparing with other fusion schemes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.14 no.1
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• pp.39-47
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• 1996

This paper is to provide land cover classification techniques for large area ranged in different pathos by classifying Landsat TM data of Jeonnam province. The analyses proceeded by individual scene because acquired dates are not same in different pathes. In this processing, troubles had happened something like variation of classes can be classified in two scenes and choice problem about overlapped area. Since spatial effects in large area affect data values, it was difficult to make a selection of classes and training fields. we could present a solution about these problems by trial and error method, and found that Bayesian maximum likelihood classification and majority filtering were effective to improve classification accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.272-287
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• 2016

Recently, various and effective contrast based salient object detection models to focus on a single target have been proposed. However, there is a lack of research on detection of multiple objects, and also it is a more challenging task than single target process. In the multiple target problem, we are confronted by new difficulties caused by distinct difference between properties of objects. The characteristic of existing models depending on the global maximum distribution of data point would become a drawback for detection of multiple objects. In this paper, by analyzing limitations of the existing methods, we have devised three main processes to detect multiple salient objects. In the first stage, regional features are extracted from over-segmented regions. In the second stage, the regional features are categorized into homogeneous cluster using the mean-shift algorithm with the kernel function having various sizes. In the final stage, we compute saliency scores of the categorized regions using only spatial features without the contrast features, and then all scores are integrated for the final salient regions. In the experimental results, the scheme achieved superior detection accuracy for the SED2 and MSRA-ASD benchmarks with both a higher precision and better recall than state-of-the-art approaches. Especially, given multiple objects having different properties, our model significantly outperforms all existing models.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.280-283
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• 2009

To improve coding performance of scalable video coding which is an emerging video coding standard as an extension of H.264/AVC, SVC uses not only intra prediction and inter prediction but inter-layer prediction. This causes a problem that computational complexity is increased. In this paper, we propose an efficient intra prediction mode decision method in spatial enhancement layer to reduce the computational complexity. The proposed method selects Inra_BL mode using RD cost of Intra_BL in advance. After that, intra mode is decided by only comparing DC modes. Experimental results show that the proposed method reduces 59% of the computation complexity of intra prediction coding, while the degradation in video quality is negligible.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06b
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• pp.240-245
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• 2008

컴퓨터 그래픽스에서 많은 광원들을 포함하는 장면을 사실적으로 렌더링하기 위해서는, 많은 양의 조명 계산을 수행해야 한다. 다수의 광원들로부터 빠르게 조명 계산을 하기 위해 많이 사용되는 기법 중에 몬테 카를로(Monte Carlo) 기법이 있다. 본 논문은 이러한 몬테 카를로(Monte Carlo) 기법을 기반으로, 다수의 광원들을 효과적으로 샘플링 할 수 있는 새로운 중요도 샘플링 기법을 제안한다. 제안된 기법의 두 가지 핵심 아이디어는 첫째, 장면 내에 다수의 광원이 존재하여도 어떤 특정 지역에 많은 영향을 주는 광원은 일부인 경우가 많다는 점이고 두 번째는 공간 일관성(spatial coherence)이 낮거나 그림자 경계 지역에 위치한 픽셀들은 영향을 받는 주요 광원이 서로 다르다는 점이다. 제안된 기법은 이러한 관찰에 착안하여 특정 지역에 광원이 기여하는 정도를 평가하고 이에 비례하게 확률 밀도 함수(PDF: Probability Density Function)를 결정하는 방법을 제안한다. 이를 위하여 이미지 공간상에서 픽셀들을 클러스터링(clustering)하고 클러스터 구조를 기반으로 대표 샘플을 선정한다. 선정된 대표 샘플들로부터 광원들의 기여도를 평가하고 이를 바탕으로 클러스터 단위의 확률 밀도 함수를 결정하여 최종 렌더링을 수행한다. 본 논문이 제안하는 샘플링 기법을 적용했을 때 전통적인 샘플링 방식과 비교하여 같은 샘플링 개수에서 노이즈(noise)가 적게 발생하는 좋은 화질을 얻을 수 있었다. 제안된 기법은 다수의 조명과 다양한 재질, 복잡한 가려짐이 존재하는 장면을 효과적으로 표현할 수 있다.

• Advances in materials Research
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• v.5 no.4
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• pp.245-261
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• 2016

Thermo-mechanical buckling problem of functionally graded (FG) nanoplates supported by Pasternak elastic foundation subjected to linearly/non-linearly varying loadings is analyzed via the nonlocal elasticity theory. Two opposite edges of the nanoplate are subjected to the linear and nonlinear varying normal stresses. Elastic properties of nanoplate change in spatial coordinate based on a power-law form. Eringen's nonlocal elasticity theory is exploited to describe the size dependency of nanoplate. The equations of motion for an embedded FG nanoplate are derived by using Hamilton principle and Eringen's nonlocal elasticity theory. Navier's method is presented to explore the influences of elastic foundation parameters, various thermal environments, small scale parameter, material composition and the plate geometrical parameters on buckling characteristics of the FG nanoplate. According to the numerical results, it is revealed that the proposed modeling can provide accurate results of the FG nanoplates as compared some cases in the literature. Numerical examples show that the buckling characteristics of the FG nanoplate are related to the material composition, temperature distribution, elastic foundation parameters, nonlocality effects and the different loading conditions.

• Structural Engineering and Mechanics
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• v.34 no.4
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• pp.491-505
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• 2010

A computational analysis of the nonlinear free vibration of corrugated annular plates with shallow sinusoidal corrugations under uniformly static ambient temperature is examined. The governing equations based on Hamilton's principle and nonlinear bending theory of thin shallow shell are established for a corrugated plate with a concentric rigid mass at the center and rotational springs at the outer edges. A simple harmonic function in time is assumed and the time variable is eliminated from partial differential governing equations using the Kantorovich averaging procedure. The resulting ordinary equations, which form a nonlinear two-point boundary value problem in spatial variable, are then solved numerically by shooting method, and the temperature-dependent characteristic relations of frequency vs. amplitude for nonlinear vibration of heated corrugated annular plates are obtained. Several numerical results are presented in both tabular and graphical forms, which demonstrate the accuracy of present method and illustrate the amplitude frequency dependence for the plate under such parameters as ambient temperature, plate geometry, rigid mass and elastic constrain.

• Journal of Biomedical Engineering Research
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• v.31 no.1
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• pp.40-49
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• 2010

A rule weight -based fuzzy classification model is proposed to analyze the patterns of admission-discharge of patients as a previous research for differential diagnosis of dyspnea. The proposed model is automatically generated from a labeled data set, supervised learning strategy, using three procedure methodology: i) select fuzzy partition regions from spatial distribution of data; ii) generate fuzzy membership functions from the selected partition regions; and iii) extract a set of candidate rules and resolve a conflict problem among the candidate rules. The effectiveness of the proposed fuzzy classification model was demonstrated by comparing the experimental results for the dyspnea patients' data set with 11 features selected from 55 features by clinicians with those obtained using the conventional classification methods, such as standard fuzzy classifier without rule weights, C4.5, QDA, kNN, and SVMs.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.10
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• pp.740-751
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• 2009

Much research on semantic geographic information systems that incorporating the Semantic Web and geographic information has been actively studied. However, the existing geographic information systems have a system dependency problem that users can input and retrieve non-spatial information only in a specific system. It also causes difficulty in providing rich services. Therefore, this paper proposes an implementation model for population of Geo-ontology from non-structured Web resources. The proposed model can populate instances for Web ontology independently of systems, and thus it enables a richer Web service development. Finally, this paper shows the prototype that populates instances including a Geo-ontology building example for a University selected as an application domain.

• Journal of the Korean Applied Science and Technology
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• v.22 no.2
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• pp.182-190
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• 2005

The propagation of light radiation within tissues is an important problem that confronts the dosimetry of therapeutic laser delivery and the development of diagnostic spectroscopy. In the clinical application of photodynamic therapy(PDT) and in photobiology, the photon deposition within a tissue determines the spatial distribution of photochemical reactions. Scattered light is measured as a function of the distance (r) between the axis of the incident beam and the detection spot. Consequently, knowledge of the photosensitizer(Chlorophyll-a) function that characterizes a phantom is important. To obtain the results of scattering coefficients(${\mu}s$) of a turbid material from diffusion described by experimental approach. It was measured the energy fluency of photon radiation at the position of penetration depth. From fluorescence experimental method obtained the analytical expression for the scattered light as the values of $(I\;/I_o)_{wavelength}$ vs the distance between the center of the incident beam and optical fiber in terms of the condition of "in situ spectroscopy(optically thick)" and real time by fluorometric measurements.