• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.957-964
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• 2016

Acquisition of reliable depth maps is a critical requirement in many applications such as 3D videos and free-viewpoint TV. Depth information can be obtained from the object directly using physical sensors, such as infrared ray (IR) sensors. Recently, Time-of-Flight (ToF) range camera including KINECT depth camera became popular alternatives for dense depth sensing. Although ToF cameras can capture depth information for object in real time, but are noisy and subject to low resolutions. Recently, filter-based depth up-sampling algorithms such as joint bilateral upsampling (JBU) and noise-aware filter for depth up-sampling (NAFDU) have been proposed to get high quality depth information. However, these methods often lead to texture copying in the upsampled depth map. To overcome this limitation, we formulate a convex optimization problem using higher order regularization for depth map upsampling. We decrease the texture copying problem of the upsampled depth map by using edge weighting term that chosen by the edge information. Experimental results have shown that our scheme produced more reliable depth maps compared with previous methods.

• The Journal of Engineering Geology
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• v.28 no.3
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• pp.379-395
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• 2018

A walking trail environment can be divided into the upper part of the trail, the trail itself, and the lower part of the trail. In this study, based on field investigations, we developed a risk index for trails by considering human/societal factors that affect each of these three trail environments. A checklist was developed for field investigations, and checklist items were scored through relative importance analysis. The relative weights of items were analyzed using the AHP (Analytic Hierarchy Process) technique, revealing that the upper environment of a trail is twice as important as the rest of the environment. The importance and score of items belonging to each environment were determined. We define the risk index as the sum of the item scores. Weights were added using data from existing investigations including landslides risk rating and designated risk steep slopes. The risk index has a maximum value of 200, and the maximum and minimum calculated scores of 335 risk sections were 159 and 64.2, respectively. As a result of comparative analysis between field observations and risk index calculations, most sections at relatively low risk had risk values less than 100, and sections with high risks or that had been the site of accident yielded scores that exceeded 140.

• Proceedings of the Korea Technology Innovation Society Conference
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• 1999.05a
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• pp.539-563
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• 1999

이 논문은 정보통신정책 목표와의 연관성 속에서 정보통신연구개발사업의 우선순위를 설정함과 아울러 비용효과성에 바탕을 둔 적정 자원배분 도출하는데 주안점을 두고 있다. 복합적인 목표를 가진 연구개발사업에 대해 사업부문별 그리고 기술분야별로 객관적이면서도 설득력있는 자원배분지침을 마련하기 위하여 본 연구는 다기준의사결정(MCDA: Multi-criteria Decision Analysis) 방법을 채택하고 있다. 이 방법론에서는 사업의 목표와 우선순위 판단기준 및 사업대안이 계층적으로 연계된 분석구조를 설계하여 사업대안의 우선순위를 먼저 설정하고, 여기에 정수계획법(Integer Programming)을 결합하여 사업의 목표와 연계된 비용-편익 관계(Cost-benefit relationship)를 최적화하는 바탕 위에서 사업대안별 자원배분 시나리오를 제시하게 된다. 이러한 절차로 사업부문별 및 기술분야별로 각각 도출된 8개의 자원배분 시나리오는 자원배분 경향치의 안정성(Stability) 분석과 자금지원의 과부족에 대한 현실적 적합성(Relevance) 분석을 거쳐 최종적으로 하나의 적정 자원배분방안으로 수렴되도록 하였다. 우선순위 설정에 기초가 되는 사업대안의 편익에 대한 자료는 전문가의 정성적 판단을 통해 수집되었는데, 이를 위해 정보통신기술 부문에서 활동 중인 중견 이상의 총 58명의 산학연 전문가를 대상으로 한 조사를 실시하였다. 먼저, 기초기반ㆍ전략기술개발사업, 연구ㆍ기술인력양성사업, 산업응용기술개발사업, 기술기반조성사업 등 4대 사업부문에 대해서는 (ⅰ) 정보통신 기술능력의 축적, (ⅱ) 정보통신산업의 경쟁력 강화, (ⅲ) 정보통신기반의 기술고도화, (ⅳ) 정보화를 위한 기술역량의 제고 등 주요 사업의 편익을 나타내는 4개 기준으로 우선 순위를 판단하였고, 정보통신망기술, 전파 및 RF 기술, 정보처리기술, 반도체 소자/설계 기술 등 13개 기술분야에 대해서는 (ⅰ) 공공정책적 임무에 대한 기여, (ⅱ) 기술자립기반의 확충, (ⅲ) 기술발전성과 기술적 파급효과, (ⅳ) 기술적 산물의 시장잠재력 등 기술분야 연구개발을 통한 편익을 나타내는 4개 기준으로 우선순위를 판단하였다. 우선순위는 사업대안에 대한 가중치로 표시되었고, 적정 자원배분방안은 추정된 총예산 규모에 따라 지원수준에 대한 일정한 제약조건 하에서 비용-편익 관계에 따른 자원의 최적 할당량으로 제시되었다. 본 연구는 총예산 규모의 가변성, 사업 및 기술분야 대안의 분류체계에 대한 공감대 부족, 사업목표의 상호연관성과 우선순위 판단기준의 부분적 중첩성 등 여러 제약요인이 있어 도출된 구체적인 수치보다는 방향성에 더 큰 의미를 부여하는 것이 바람직하다. 그러나, 이러한 연구의 한계에도 불구하고 도출된 우선순위와 적정 자원배분방안은 문제해결의 실행타당성을 감안하여 비교적 객관적이고 균형있는 결과로 판단된다.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.385-394
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• 2009

Face tracking and recognition are difficult problems because the face is a non-rigid object. The main reasons for the failure to track and recognize the faces are the changes of a face pose and environmental illumination. To solve these problems, we propose a nonlinear manifold framework for the face pose and the face illumination normalization processing. Specifically, to track and recognize a face on the video that has various pose variations, we approximate a face pose density to single Gaussian density by PCA(Principle Component Analysis) using images sampled from training video sequences and then construct the GMM(Gaussian Mixture Model) for each person. To solve the illumination problem for the face tracking and recognition, we decompose the face images into the reflectance and the illuminance using the SSR(Single Scale Retinex) model. To obtain the normalized reflectance, the reflectance is rescaled by histogram equalization on the defined range. We newly approximate the illuminance by the trained manifold since the illuminance has almost variations by illumination. By combining these two features into our manifold framework, we derived the efficient face tracking and recognition results on indoor and outdoor video. To improve the video based tracking results, we update the weights of each face pose density at each frame by the tracking result at the previous frame using EM algorithm. Our experimental results show that our method is more efficient than other methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.107-114
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• 2005

Edge enhanced image is needed for processing images for special purpose such as a circuit diagram or a design composed of lines. Error diffusion halftoning, among digital halftoning methods to represent a continuous grayscale image for the binary output device such as printers, facsimiles, LCD televisions and etc. also makes edges of objects blurred. This paper proposes the method to enhance the edge of a binary image for the binary output device as well as a circuit diagram or a design. Based on that the human eyes perceive the local average luminance rather than the pixel's luminance itself, the proposed system uses a local activitymeasure (LAM), which is the difference between a pixel luminance and the average of its $3{\times}3$ neighborhood pixels' luminances weighted according to the spatial positioning. The system also usesinformation of edge enhancement(IEE), which is computed from the LAM multiplied by the average luminance. The IEE is added to the quantizer's input pixel and feeds into the halftoning quantizer. The quantizer produces the halftone image having the enhanced edge. The simulation results show that the proposed method produces more fine halftoning images than conventional methods due to the enhanced edges. Also the performance of the proposed method is compared with that of the conventional method by measuring the edge correlation and the local average accordance over a range of viewing distances.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.207-216
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• 2013

The aim of this study is to design a classifier for sleep stage analysis and select important feature set which shows sleep stage well based on physiological signals during sleep. Sleep has a significant effect on the quality of human life. When people undergo lack of sleep or sleep-related disease, they are likely to reduced concentration and cognitive impairment affects, etc. Therefore, there are a lot of research to analyze sleep stage. In this study, after acquisition physiological signals during sleep, we do pre-processing such as filtering for extracting features. The features are used input for the new combination algorithm using genetic algorithm(GA) and neural networks(NN). The algorithm selects features which have high weights to classify sleep stage. As the result of this study, accuracy of the algorithm is up to 90.26% with electroencephalography(EEG) signal and electrocardiography(ECG) signal, and selecting features are alpha and delta frequency band power of EEG signal and standard deviation of all normal RR intervals(SDNN) of ECG signal. We checked the selected features are well shown that they have important information to classify sleep stage as doing repeating the algorithm. This research could use for not only diagnose disease related to sleep but also make a guideline of sleep stage analysis.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.65-73
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• 2017

In this paper, we propose a stereo matching method to improve the image quality at the hole and the disparity discontinuity regions. The stereo matching method extracts disparity map finding corresponding points between stereo image pair. However conventional stereo matching methods have a problem about the tradeoff between accuracy and precision with respect to the length of the baseline of the stereo image pair. In addition, there are hole and disparity discontinuity regions which are caused by textureless regions and occlusion regions of the stereo image pair. The proposed method extracts initial disparity map improved at disparity discontinuity and miss-matched regions using modified AD-Census-Gradient method and adaptive weighted cost aggregation. And then we conduct the disparity map refinement to improve at miss-matched regions, while also improving the accuracy of the image. Experimental results demonstrate that the proposed method produces high-quality disparity maps by successfully improving miss-matching regions and accuracy while maintaining matching performance compared to existing methods which produce disparity maps with high matching performance. And the matching performance is increased about 3.22(%) compared to latest stereo matching methods in case of test images which have high error ratio.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.17-25
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• 2007

In most electronic imaging applications, image with high resolution(HR) are desired. HR means that pixel density within an image is high, and therefore HR image can offer more details that may be critical in various applications. Digital images that are captured by CCD and CMOS cameras usually have a very low resolution, which significantly limits the performance of image recognition systems. Image super-resolution techniques can be applied to overcome the limits of these imaging systems. Super-resolution techniques have been proposed to increase the resolution by combining information from multiple images. To techniques were consisted of the registration algorithm for estimation and shift, the nearest neighbor interpolation using weight of acquired frames and presented frames. In this paper, it is proposed the image interpolation techniques using the wavelet base function. This is applied to embody a correct edge image and natural image when expend part of the still image by applying the wavelet base function coefficient to the conventional Super-Resolution interpolation method. And the proposal algorithm in this paper is confirmed to improve the image applying the nearest neighbor interpolation algorithm, bilinear interpolation algorithm.,bicubic interpolation algorithm through the computer simulation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.50-58
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• 2008

In this paper, we propose a color transient improvement (CTI) algorithm based on image fusion to improve the color transient in the television(TV) receiver or in the MPEG decoder. Video image signals are composed of one luminance and two chrominance components, and the chrominance signals have been more band-limited than the luminance signals since the human eyes usually cannot perceive changes in chrominance over small areas. However, nowadays, as the advanced media like high-definition TV(HDTV) is developed, the blurring of color is perceived visually and affects the image quality. The proposed CTI method improves the transient of chrominance signals by exploiting the high-frequency information of the luminance signal. The high-frequency component extracted from the luminance signal is modified by spatially adaptive weights and added to the input chrominance signals. The spatially adaptive weight is estimated to minimize the ${\iota}_2-norm$ of the error between the original and the estimated chrominance signals in a local window. Experimental results with various test images show that the proposed algorithm produces steep and natural color edge transition and the proposed method outperforms conventional algorithms in terms of both visual and numerical criteria.

• Journal of KIISE:Databases
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• v.32 no.3
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• pp.263-275
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• 2005

In a large DNA database, indexing techniques are widely used for rapid approximate sequence searching. However, most indexing techniques require a space larger than original databases, and also suffer from difficulties in seamless integration with DBMS. In this paper, we suggest a space-efficient and disk-based indexing and query processing algorithm for approximate DNA sequence searching, specially exact match queries, wildcard match queries, and k-mismatch queries. Our indexing method places a sliding window at every possible location of a DNA sequence and extracts its signature by considering the occurrence frequency of each nucleotide. It then stores a set of signatures using a multi-dimensional index, such as R*-tree. Especially, by assigning a weight to each position of a window, it prevents signatures from being concentrated around a few spots in index space. Our query processing algorithm converts a query sequence into a multi-dimensional rectangle and searches the index for the signatures overlapped with the rectangle. The experiments with real biological data sets revealed that the proposed method is at least three times, twice, and several orders of magnitude faster than the suffix-tree-based method in exact match, wildcard match, and k- mismatch, respectively.