• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.1-10
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• 2007

This paper proposes a new indexing mechanism for MPEG-7 visual descriptors, especially Dominant Color and Contour Shape descriptors, that guarantees an efficient similarity search for the multimedia database whose visual meta-data are represented with MPEG-7. Since the similarity metric used in the Dominant Color descriptor is based on Gaussian mixture model, the descriptor itself could be transform into a color histogram in which the distribution of the color values follows the Gauss distribution. Then, the transformed Dominant Color descriptor (i.e., the color histogram) is indexed in the proposed indexing mechanism. For the indexing of Contour Shape descriptor, we have used a two-pass algorithm. That is, in the first pass, since the similarity of two shapes could be roughly measured with the global parameters such as eccentricity and circularity used in Contour shape descriptor, the dissimilar image objects could be excluded with these global parameters first. Then, the similarities between the query and remaining image objects are measured with the peak parameters of Contour Shape descriptor. This two-pass approach helps to reduce the computational resources to measure the similarity of image objects using Contour Shape descriptor. This paper also proposes two integration schemes of visual descriptors for an efficient retrieval of multimedia database. The one is to use the weight of descriptor as a yardstick to determine the number of selected similar image objects with respect to that descriptor, and the other is to use the weight as the degree of importance of the descriptor in the global similarity measurement. Experimental results show that the proposed indexing and integration schemes produce a remarkable speed-up comparing to the exact similarity search, although there are some losses in the accuracy because of the approximated computation in indexing. The proposed schemes could be used to build a multimedia database represented in MPEG-7 that guarantees an efficient retrieval.

• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.551-562
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• 2000

Content-based image retrieval system retrieves an image from a database using visual features. Among approaches to express visual aspects in queries, 'query by sketch' is most convenient and expressive. However, every 'query by sketch' system has the query imperfectness problem. GContent-based image retrieval system retrieves an image from a database using visual features. Among approaches to express visual aspects in queries, 'query by sketch' is most convenient and expressive. However, every 'query by sketch' system has the query imperfectness problem. Generally, the query image produced by a user is different from the intended target image. To overcome this problem, many image retrieval systems use the spatial relationships of the objects, instead of pixel coordinates of the objects. In this paper, a query-converting algorithm for an image retrieval system, which uses the spatial relationship of every two objects as an image feature, is proposed. The proposed algorithm converts the query image into a graph that has the minimum number of edges, by eliminating every transitive edge. Since each edge in the graph represents the spatial relationship of two objects, the elimination of unnecessary edges makes the retrieval process more efficient. Experimental results show that the proposed algorithm leads the smaller number of comparison in searching process as compared with other algorithms that do not guarantee the minimum number of edges.

• Journal of KIISE:Software and Applications
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• v.29 no.12
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• pp.947-956
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• 2002

It is advantageous to use XML in developing user interfaces, since XML is independent from platforms and languages and it is easy to learn and use. The existing XML-based languages do not adopt formal model, and they are developed in ad hoc manner. Moreover, they provide limited facilities to handle user events, and combine user interface components with internal logics. In this paper, we introduce an extended MVP (EMVP) model, which is extended from MVP (Model-View-Presenter), and XUIML, which is a new XML application based on the EMVP to support user interface. XUIML provides useful methods to build user interface, including methods to describe actions on user events, data flows between objects, and internal logics. The XUIML system provides two style editors - text editor and graphic editor. It also provides two code generators. One generates Java source, and the other generate C# code from XUIML document. The XUIML graphic editor allows users to manipulate XML elements directly, and we can gain high productivity with the graphic editor.

• Journal of KIISE:Databases
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• v.33 no.5
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• pp.486-494
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• 2006

A web page can be represented by syntactically different URLs. URL normalization is a process of transforming URL strings into canonical form. Through this process, duplicate URL representations for a web page can be reduced significantly. A number of normalization methods have been heuristically developed and used, and there has been no study on analyzing the normalization methods systematically. In this paper, we give a way to evaluate normalization methods in terms of efficiency and effectiveness of web applications, and give users guidelines for selecting appropriate methods. To this end, we examine all the effects that can take place when a normalization method is adopted to web applications, and describe seven metrics for evaluating normalization methods. Lastly, the evaluation results on 12 normalization methods with the 25 million actual URLs are reported.

• Journal of KIISE:Databases
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• v.30 no.2
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• pp.125-133
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• 2003

In this paper we propose an efficient content-based image retrieval method using the color and wavelet based texture features. The color features are obtained from soft-color histograms of the global image and the wavelet-based texture features are obtained from the invariant moments of the high-pass sub-band through the spatial-frequency analysis of the wavelet transform. The proposed system, called a color and texture based two-step retrieval(CTBTR), is composed of two-step query operations for an efficient image retrieval. In the first-step matching operation, the color histogram features are used to filter out the dissimilar images quickly from a large image database. The second-step matching operation applies the wavelet based texture features to the retained set of images to retrieve all relevant images successfully. The experimental results show that the proposed algorithm yields more improved retrieval accuracy with computationally efficiency than the previous methods.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.6
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• pp.657-668
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• 2002

Software life cycle consists of requirement analysis, design, implementation, and maintenance phases, and the product of each phase has various format. The UML normalizes such products, and the class diagram, use case diagram, activity diagram and collaboration diagram are usually used for the requirement analysis phase. Because most of UML development tools store such diagrams in a file, there nay be some difficulties of information retrieval and co-work among users. To cope with the difficulties, this paper proposes a database supported methodology to store and manage the diagrams produced by the requirement analysis. In this methodology, the constituents of class, use case, activity and collaboration diagram are first analyzed and then transformed in the form of relational fables. The constituents of such diagrams are stored as tables in a database, and can be easily retrieved from the database by using some queries. This database supported methodology provides the concurrent sharing and high reuse of diagrams.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.344-356
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• 2001

This paper deals with the subsequence searching problem under time-warping in sequence databases. Our work is motivated by the observation that subsequence searches slow down quadratically as the average length of data sequences increases. To resolve this problem, the Segment-Based Approach for Subsequence Searches (SBSS) is proposed. The SBASS divides data and query sequences into a series of segments, and retrieves all data subsequences that satisfy the two conditions: (1) the number of segments is the same as the number of segments in a query sequence, and (2) the distance of every segment pair is less than or equal to a tolerance. Our segmentation scheme allows segments to have different lengths; thus we employ the time warping distance as a similarity measure for each segment pair. For efficient retrieval of similar subsequences, we extract feature vectors from all data segments exploiting their monotonically changing properties, and build a spatial index using feature vectors. Using this index, queries are processed with the four steps: (1) R-tree filtering, (2) feature filtering, (3) successor filtering, and (4) post-processing. The effectiveness of our approach is verified through extensive experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.11
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• pp.2264-2275
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• 1994

In this paper, image compression based on neural networks is presented with block classification and coding. Multilayer neural networks with error back-propagation learning algorithm are used to transform the normalized image date into the compressed hidden values by reducing spatial redundancies. Image compression can basically be achieved with smaller number of hidden neurons than the numbers of input and output neurons. Additionally, the image blocks can be grouped for adaptive compression rates depending on the characteristics of the complexity of the blocks in accordance with the sensitivity of the human visual system(HVS). The quantized output of the hidden neuron can also be entropy coded for an efficient transmission. In computer simulation, this approach lie in the good performances even with images outside the training set and about 25:1 compression rate was achieved using the entropy coding without much degradation of the reconstructed images.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.3
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• pp.248-259
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• 2001

This paper proposes a human action recognition scheme to recognize nonverbal human communications automatically. Based on the principle that a human body action can be defined as a combination of multiple articulation movements, we use the method of inferencing stochastic grammars to understand each human actions. We measure and quantize each human action in 3D world-coordinate, and make two sets of 4-chain-code for xy and zy projection plane. Based on the fact that the neighboring information among articulations is an essential element to distinguish actions, we designed a new stochastic inference procedure to apply the neighboring information of hands. Our proposed scheme shows better recognition rate than that of other general stochastic inference procedures. ures.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.2922-2931
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• 1999

In this paper, we propose a new framework for scalable media object to adapt the various QoS requirements in the heterogeneous networking environment. An MPEG-2 video is split into a set of scalable media objects in terms of temporal scaling and fidelity scaling. The portion of the scalable media objects is selectively delivered to adapt the QoS requirement. This framework can satisfy the various QoS requirements on bandwidth, even though the clients share a multipoint channel. By analysis on the rate-distortion characteristics of scalable media object framework, we shows our approach is feasible to support the various QoS requirements.