• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.135-139
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• 2009

In this paper we present INCUI, a user interface based on natural view of physical user interface of target devices and services in pervasive computing environment. We present a concept of Intuitively Natural and Consistent User Interface (INCUI) consisted of an image of physical user interface and a description XML file. Then we elaborate how INCUI template can be used to consistently map user interface components structurally and visually. We describe the process of INCUI mapping and a novel mapping method selection architecture based on domain size, types of source and target INCUI. Especially we developed and applied an extended LCS-based algorithm using prefix/postfix/synonym for similarity calculation.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.407-412
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• 2008

Color segmentation is one of the most challenging problems in image processing especially in case of handling the images with cluttered background. Great amount of color segmentation methods have been developed and applied to real problems. In this paper, we suggest a new methodology. Our approach is focused on background extraction, as a complimentary operation to standard foreground object segmentation, using self-organizing feature selective property of unsupervised self-learning paradigm based on the competitive algorithm. The results of our studies show that background segmentation can be achievable in efficient manner.

• Proceedings of the KIEE Conference
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• 2005.11a
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• pp.9-11
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• 2005

본 연구는 GIS 진단신뢰성 향상기술 개발을 목적으로, 16개의 인위적 결함을 이용하여 부분방전 신호를 발생시키고 검출하여 그 패턴인식 확률을 높이기 위하여 신경망에 Genetic Algorithm (GA) 을 적용하였다. 이를 위하여 다음과 같은 5가지 서로 다른 신경망 모델을 선택하였다: Back Propagation (BP), Jordan-Elman Network (JEN), Principal Component Analysis (PCA), Self-Organizing Feature Map (SOFM) 및 Support Vector Machine (SVM). 이와 같이 선택된 모델에 동일한 데이터를 학습 시키고 패턴인식 확률을 비교 및 분석하였다. 실험 결과에 의하면, BP의 인식률이 가장 높고 다음으로 JEN의 인식률이 높이 나타났으며, 후자의 경우 모든 결함에 대하여 정확한 패턴분류를 한 반면에 전자의 경우 1.8% 의 분류 오차가 발생하였다. 따라서 인식률이 높은 신경망이 더 정확한 패턴분류를 보장하지 못한다는 실험적 결과를 고려 할 때, 인식률이 높은 두 개의 모델을 선정하여 각각의 출력에 일정한 가중치를 주고 합산하여 새로운 출력을 얻는 방법을 제안한다.

• KIISE Transactions on Computing Practices
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• v.23 no.8
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• pp.481-486
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• 2017

There are many scientists who want to perform experiments in a cloud environment, and pay-per-use services allow scientists to pay only for cloud services that they need. However, it is difficult for scientists to select a suitable set of resources since those resources are comprised of various characteristics. Therefore, classification is needed to support the effective utilization of cloud resources. Thus, a dynamic resource clustering method is needed to reflect the characteristics of the application that scientists want to execute. This paper proposes a resource clustering analysis method that takes into account the characteristics of an application in a hybrid cloud environment. The resource clustering analysis applies a Self-Organizing Map and K-means algorithm to dynamically cluster similar resources. The results of the experiment indicate that the proposed method can classify a similar resource cluster by reflecting the application characteristics.

• Journal of Broadcast Engineering
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• v.2 no.1
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• pp.36-44
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• 1997

We propose 3D perspective display using elevation matrix data with 2D information overlay. This algorithm is based on ID scan-line method and we used color index of the newly developed raster map, VRRG(Vector Restored Raster Graphics). The proposed method allows the fast generation of perspective view of 3D data with 2D overlay and the fast selective display of the features of 2D overlay.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.948-955
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• 2019

As interests in 360-degree VR (Virtual Reality) video services enormously grow, compression and streaming technologies for VR video data have been rapidly developed. Quality Emphasized Region (QER) based streaming scheme has been developed as a kind of viewport-adaptive 360-degree video streaming technology for maintaining immersive experience and reducing bandwidth waste. For selecting a QER corresponding to the user's gaze coordinate, QER-based streaming scheme requires the calculation of Quality Emphasis Center (QEC) distance and signaling message delivery for requesting QER switching. QEC distance calculations require high computational complexity because of repeated calculations as many times as the number of QERs. Furthermore, the signaling message interval results in a trade-off relationship between efficient bandwidth usage and flexible QER switching. In this paper, we propose an improved QER selection algorithm based on MMT protocol to solve this problem. The proposed algorithm could achieve computational complexity reduction by using preprocessed QER_ID_MAP. Also, flexible QER switching could be achieved, as well as efficient bandwidth utilization by an adaptive adjustment of the signaling interval.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.4
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• pp.508-516
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• 2016

When GPS signals are not available, a relative localization can be alternatively used to represent the topological relationship between mobile nodes. A relative location map of a network can be constructed by using the distance information between all the pairs of nodes in the network. If a network is large, a number of small local maps are individually constructed and are merged to obtain the whole map. However, this approach may result in a high computation and communication overhead. In this paper, we propose a reference-node selection scheme for relative localization map construction, which chooses a subset of nodes as a reference node that is supposed to construct local maps. The scheme is a greedy algorithm that iteratively chooses nodes with high degree as a reference node until the chosen local maps are successfully merged with a sufficient number of common nodes between nearby local maps. The simulation results indicate that the proposed scheme achieves higher localization accuracy with a reduced computational overhead.

• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.793-802
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• 2004

Users in 3D virtual environment get limited information which contains mostly images. It is the main reason for users getting lost during their Navigation. Various studies of Navigation-Aid have been done in order to solve this problem. In this study, we applied Topic Maps, which is one of semantic Web techniques, to the navigation in a 3D virtual environment. Topic Maps construct semantic linking maps through defining the relations between topics. Experiments in which Topic Map based Navigation-Aid was applied have shown that the Navigation-Aid was effective when the subjects find a detailed target rather than a highly represented one. Also, offering information around the target helped the users to find the target when they navigated without having specific targets.

• Journal of Digital Contents Society
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• v.7 no.4
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• pp.287-294
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• 2006

Mass-customization is fast growing a segment of the apparel market. 2D Virtual wearing system is one of visual support tools that make possible to sell apparel before producing and reduce the time and costs related to product development and manufacturing in the world of apparel mass-customization. This paper is related to fabric color mapping method for 2D image-based virtual wearing system. In proposed method, clothing shape section of interest is segmented from a clothes model image using a region growing method, and then mapping a new fabric color selected by user into it based on its intensity difference map is processed. With the proposed method in 2D virtual wearing system, regardless of color or intensity of model clothes, it is possible to virtually change the fabric color with holding the illumination and shading properties of the selected clothing shape section, and also to quickly and easily simulate, compare, and select multiple fabric color combinations for individual styles or entire outfits.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.362-370
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• 2001

In this paper, we proposed multispectral image compression method using CIP (classified inter-channel prediction) and SVQ (selective vector quantization) in wavelet domain. First, multispectral image is wavelet transformed and classified into one of three classes considering reflection characteristics of the subband with the lowest resolution. Then, for a reference channel which has the highest correlation and the same resolution with other channels, the variable VQ is performed in the classified intra-channel to remove spatial redundancy. For other channels, the CIP is performed to remove spectral redundancy. Finally, the prediction error is reduced by performing SVQ. Experiments are carried out on a multispectral image. The results show that the proposed method reduce the bit rate at higher reconstructed image quality and improve the compression efficiency compared to conventional methods. Index Terms-Multispectral image compression, wavelet transform, classfied inter-channel prediction, selective vetor quantization, subband with lowest resolution.