• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.113-120
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• 2004

In this paper, we propose an efficient feature extraction and image retrieval algorithm for content-based retrieval method. First, we extract the object using Gaussian edge detector for input image which is key frames of MPEG video and extract the object features that are location feature, distributed dimension feature and invariant moments feature. Next, we extract the characteristic color feature using the proposed HAQ(Histogram Analysis md Quantization) algorithm. Finally, we implement an retrieval of four features in sequence with the proposed matching method for query image which is a shot frame except the key frames of MPEG video. The purpose of this paper is to propose the novel content-based image retrieval algerian which retrieves the key frame in the shot boundary of MPEG video belonging to the scene requested by user. The experimental results show an efficient retrieval for 836 sample images in 10 music videos using the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.5
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• pp.58-64
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• 2001

Recently many informations are transmitted ,md stored as video data, and they are on the rapid increase because of popularization of high performance computer and internet. In this paper, to retrieve video data, shots are found through analysis of video stream and the method of detection of key frame is studied. Finally users can retrieve the video efficiently. This Paper suggests a new feature that is robust to object movement in a shot and is not sensitive to change of color in boundary detection of shots, and proposes the characterizing value that reflects the characteristic of kind of video (movie, drama, news, music video etc,). The key frames are pulled out from many frames by using the local minima and maxima of differential of the value. After original frame(not de image) are reconstructed for key frame, indexing process is performed through computing parameters. Key frames that arc similar to user's query image arc retrieved through computing parameters. It is proved that the proposed methods are better than conventional method from experiments. The retrieval accuracy rate is so high in experiments.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.17-26
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• 2005

With the rapidly Slowing information, the research on the effcient information retrieval is increasing. Most of the retrieval systems for domestic cultural assets on the web have adopted a keyword-based search method. Those systems have required users to know the exact information about cultural assets such as name, keyword, etc. However, it is not easy to search the cultural assets with little information or only a remembrance of the shape. In this paper, we propose the retrieval system for cultural assets using both ontology-based and sketch-based search method to solve the Problems of existing systems. Our retrieval system allows users to use both text and sketch for a Query regardless of the type of information about cultural assets and to search in results using the ontology.

• Journal of IKEEE
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• v.14 no.3
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• pp.224-231
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• 2010

Automatic detection of objects in images has been one of core challenges in the areas such as computer vision and pattern analysis. Especially, with the recent deployment of personal mobile devices such as smart phone, such technology is required to be transported to them. Usually, these smart phone users are equipped with devices such as camera, GPS, and gyroscope and provide various services through user-friendly interface. However, the smart phones fail to give excellent performance due to limited system resources. In this paper, we propose a new scheme to improve object recognition performance based on pre-computation and simple local features. In the pre-processing, we first find several representative parts from similar type objects and classify them. In addition, we extract features from each classified part and train them using regression functions. For a given query image, we first find candidate representative parts and compare them with trained information to recognize objects. Through experiments, we have shown that our proposed scheme can achieve resonable performance.

• Journal of Korea Spatial Information System Society
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• v.11 no.3
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• pp.19-30
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• 2009

Recent development in wireless communication technology and mobile equipment like PDA, cellular phone and GPS makes location-based services (LBSs) popular. However, because, in the LBSs, users continuously request a query to LBS servers by using their exact locations, privacy information could be in danger. Therefore, a mechanism for users' privacy protection is required for the safe and comfortable use of LBSs by mobile users. For this, this paper propose a grid-based cloaking area creation scheme supporting continuous LBSs. The proposed scheme creates a cloaking area rapidly by using grid-based cell expansion to efficiently support the continuous LBSs. In addition, to generate a cloaking area which makes the exposure probability of a mobile user to a minimum, we compute a privacy protection degree by granting weights to mobile users. Finally, we show from a performance analysis that our cloaking scheme outperforms the existing cloaking schemes, in terms of service time, privacy protection degree.

• Spatial Information Research
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• v.18 no.4
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• pp.141-149
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• 2010

One of recent trends in Web-based GIS is the system development using FOSS (Free and Open Source Software). Open Source software is independent from the technologies of commercial software and can increase the reusability and extensibility of existing systems. In this study, we developed a Web-based GIS for interactive visualization of geographic information using Google Earth and spatial DBMS(database management system). Google Earth Plug-in and Google Earth API(application programming interface) were used to embed a geo-browser in the Web browser. In order to integrate the Google Earth with a spatial DBMS, we implemented a KML(Keyhole Markup Language) generator for transmitting server-side data according to user's query and converting the data to a variety of KML for geovisualization on the Web. Our prototype system was tested using time-series of LAI(leaf area index), forest map, and crop yield statistics. The demonstration included the geovisualization of raster and vector data in the form of an animated map and a 3-D choropleth map. We anticipate our KML generator and system framework will be extended to a more comprehensive geospatial analysis system on the Web.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.971-980
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• 2002

As the importance of knowledge management is being recognized, there is a significant amount of increase for interest in data warehousing. On-Line Analytical Processing (OLAP) systems can effectively make use of data warehouses. Although there are many commercial OLAP products, they have been developed without any kind of standard resulting in poor data exchange and difficulty in interfacing among the OLAP products. In this paper we propose an OLAP metadata interchange model that can be used among different OLAP products and have implemented an OLAP metadata interchange system that can interchange the cubes created from the metadata. XML is used for the OLAP metadata model and the user interface is Web-based, which makes it easier to interchange metadata among different OLAP products. Users can experience the different analysis environments of different products without the need to learn the complex cube creation process for each product. By extending this research to design a common query language that can be used among OLAP products, OLAP products should be able to more easily talk to one another.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1374-1385
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• 2004

The relevance feedback process uses information obtained from a user about an initially retrieved set of documents to improve subsequent search formulations and retrieval performance. In the extended Boolean model, the relevance feedback Implies not only that new query terms must be identified, but also that the terms must be connected with the Boolean AND/OR operators properly Salton et al. proposed a relevance feedback method for the extended Boolean model, called the DNF (disjunctive normal form) method. However, this method has a critical problem in generating a reformulated queries. In this study, we investigate the problem of the DNF method and propose a relevance feedback method using hierarchical clustering techniques to solve the problem. We show the results of experiments which are performed on two data sets: the DOE collection in TREC 1 and the Web TREC 10 collection.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.370-381
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• 2012

Multi-criteria result extraction is crucial in many scientific applications that support real-time stream processing, such as habitat research and disaster monitoring. Skyline evaluation is computational intensive especially over continuous time-interval data streams where each object has its own customized expiration time. In this work, we propose TI-Sky - a continuous skyline evaluation framework. To ensure correctness, the result space needs to be continuously maintained as new objects arrive and older objects expire. TI-Sky strikes a perfect balance between the costs of continuously maintaining the result space and the costs of computing the final skyline result from this space whenever a pull-based user query is received. Our key principle is to incrementally maintain a partially precomputed skyline result space - however doing so efficiently by working at a higher level of abstraction. TI-Sky's algorithms for insertion, deletion, purging and result retrieval exploit both layers of granularity. Our experimental study demonstrates the superiority of TI-Sky over existing techniques to handle a wide variety of data sets.

• Journal of the Korean Society for information Management
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• v.25 no.4
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• pp.115-129
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• 2008

Recently, as its growth and popularization, the Web is changed into the place where people express, share and debate their opinions rather than the space of information seeking. Accordingly, the needs for searching opinions expressed in the Web are also increasing. However, it is difficult to meet these needs by using a classical information retrieval system that only concerns the relevance between the user's query and documents. Instead, a more advanced system that captures subjective information through documents is required. The proposed system effectively retrieves opinionated documents by utilizing an existing information retrieval system. This paper proposes a kind of hybrid method which can utilize both a dictionary-based opinion analysis technique and a machine learning based opinion analysis technique. Experimental results show that the proposed method is effective in improving the performance.