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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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The KIPS Transactions:PartB
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Korea Information Processing Society
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Volume & Issues
Volume 11B, Issue 7 - Dec 2004
Volume 11B, Issue 6 - Oct 2004
Volume 11B, Issue 5 - Aug 2004
Volume 11B, Issue 4 - Aug 2004
Volume 11B, Issue 3 - Jun 2004
Volume 11B, Issue 2 - Apr 2004
Volume 11B, Issue 1 - Feb 2004
Volume 11, Issue 2 - 00 2004
Volume 11, Issue 1 - 00 2004
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The Large Capacity Steganography Using Adaptive Threshold on Bit Planes
Lee, Sin-Joo ; Jung, Sung-Hwan ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 395~402
DOI : 10.3745/KIPSTB.2004.11B.4.395
In this paper, we proposed a new method of the large capacity steganography using adaptive threshold on bit planes. Applying fixing threshold, if we insert information into all bit planes, all bit planes showed different image quality. Therefore, we first defined the bit plane weight to solve the fixing threshold problem. We then proposed a new adaptive threshold method using the bit plane weight and the average complexity to increase insertion capacity adaptively. In the experiment, we inserted information into the standard images with the same image quality and same insertion capacity, and we analyzed the insertion capacity and image duality. As a result, the proposed method increased the insertion capacity of about 6% and improved the image quality of about 24dB than fixed threshold method.
Color Component Analysis For Image Retrieval
Choi, Yong-Kwan ; Choi, Chul ; Park, Jang-Chun ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 403~410
DOI : 10.3745/KIPSTB.2004.11B.4.403
Recently, studies of image analysis, as the preprocessing stage for medical image analysis or image retrieval, are actively carried out. This paper intends to propose a way of utilizing color components for image retrieval. For image retrieval, it is based on color components, and for analysis of color, CLCM (Color Level Co-occurrence Matrix) and statistical techniques are used. CLCM proposed in this paper is to project color components on 3D space through geometric rotate transform and then, to interpret distribution that is made from the spatial relationship. CLCM is 2D histogram that is made in color model, which is created through geometric rotate transform of a color model. In order to analyze it, a statistical technique is used. Like CLCM, GLCM (Gray Level Co-occurrence Matrix) and Invariant Moment [2,3] use 2D distribution chart, which use basic statistical techniques in order to interpret 2D data. However, even though GLCM and Invariant Moment are optimized in each domain, it is impossible to perfectly interpret irregular data available on the spatial coordinates. That is, GLCM and Invariant Moment use only the basic statistical techniques so reliability of the extracted features is low. In order to interpret the spatial relationship and weight of data, this study has used Principal Component Analysis [4,5] that is used in multivariate statistics. In order to increase accuracy of data, it has proposed a way to project color components on 3D space, to rotate it and then, to extract features of data from all angles.
A Still Image Compression System using Bitmatrix Arithmetic Coding
Lee, Je-Myung ; Lee, Ho-Suk ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 411~420
DOI : 10.3745/KIPSTB.2004.11B.4.411
We propose a novel still image compression system, which is superior in its function than the JPEG2000 system developed by David Taubman. The system shows 40 : 1 high compression ratio using
bitmatrix subblock coding. The
bitmatrix subblock is constructed in the bitplanes by organizing the bits into subblocks composing of
matrices. The arithmetic coding performs the high compression by the bitmatrices in the subblock. The input of the system consists of a segmentation mode and a ROI(Region Of Interest) mode. In segmentation mode, the input image is segmented into a foreground consisting of letters and a background consisting of the remaining region. In ROI mode, the input image is represented by the region of interest window. The high compression ratio shows that the proposed system is competent among the JPEG2000 products currently in the market. This system also uses gray coding to improve the compression ratio.
Comparisons of MPEG-7 Texture Descriptors for Iris recognition
Choo, Hyon-Gon ; Kim, Whoi-Yul ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 421~428
DOI : 10.3745/KIPSTB.2004.11B.4.421
There are three texture descriptors in MPEG-7 : Homogeneous Texture, Edge Histogram and Texture Browsing. In this paper, a comparative analysis is presented on the capability of MPEG-7 texture descriptors for iris recognition as part of an MPEG-7 application using descriptors. Through the experiments of comparing the clustering efficiency and error distribution of the descriptors using 560 iris images, their discriminating capabilities for different iris groups are analyzed. The results show that Homogenous Texture descriptor is the best discriminator among three descriptors to recognize the iris pattern. However, compared with the conventional iris recognition methods, it needs more efforts to enhance the results.
Independent Component Analysis for Clustering Analysis Components by Using Kurtosis
Cho, Yong-Hyun ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 429~436
DOI : 10.3745/KIPSTB.2004.11B.4.429
This paper proposes an independent component analyses(ICAs) of the fixed-point (FP) algorithm based on Newton and secant method by adding the kurtosis, respectively. The kurtosis is applied to cluster the analyzed components, and the FP algorithm is applied to get the fast analysis and superior performance irrelevant to learning parameters. The proposed ICAs have been applied to the problems for separating the 6-mixed signals of 500 samples and 10-mixed images of
pixels, respectively. The experimental results show that the proposed ICAs have always a fixed analysis sequence. The results can be solved the limit of conventional ICA without a kurtosis which has a variable sequence depending on the running of algorithm. Especially. the proposed ICA can be used for classifying and identifying the signals or the images. The results also show that the secant method has better the separation speed and performance than Newton method. And, the secant method gives relatively larger improvement degree as the problem size increases.
Bio-Ontology Generation Using Object-Oriented Ontology Manager
Yang, Kyung-Ah ; Yang, Hyung-Jeong ; Yang, Jae-Dong ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 437~448
DOI : 10.3745/KIPSTB.2004.11B.4.437
This paper presents an approach to the development of bio-ontology using the Object-oriented Ontology Manager(OOM). OOM views a term of an ontology as an object which can be an instance or a concept. OOM facilitates the semi-automatic construction of ontologies by an intuitive interface and by inferencing with links among complicated and informative ontology terns. The main advantage of OOM is simple-to-use not compromising expressiveness so that ontologies in a complicated domain such as bioinformatics can be modeled intuitively. The ontologies constructed by OOM are easily exported to ontologies in other ontology languages without semantic loss because the structures of both the ontology by OOM and the ontologies in most of standard ontology languages are analogous. A translator to another standard ontology language is also provided by OOM so that the ontology can be combined with others to be applied to more complicated applications.
A Novel Model, Recurrent Fuzzy Associative Memory, for Recognizing Time-Series Patterns Contained Ambiguity and Its Application
Kim, Won ; Lee, Joong-Jae ; Kim, Gye-Young ; Choi, Hyun-Gil ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 449~456
DOI : 10.3745/KIPSTB.2004.11B.4.449
This paper proposes a novel recognition model, a recurrent fuzzy associative memory(RFAM), for recognizing time-series patterns contained an ambiguity. RFAM is basically extended from FAM(Fuzzy Associative memory) by adding a recurrent layer which can be used to deal with sequential input patterns and to characterize their temporal relations. RFAM provides a Hebbian-style learning method which establishes the degree of association between input and output. The error back-propagation algorithm is also adopted to train the weights of the recurrent layer of RFAM. To evaluate the performance of the proposed model, we applied it to a word boundary detection problem of speech signal.
Competence Ontology for Semantic Web Services Description
Oh, Ji-Hoon ; Choi, Byeong-Seok ; Jeong, Young-Sik ; Joo, Su-Chong ; Han, Sung-Kook ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 457~464
DOI : 10.3745/KIPSTB.2004.11B.4.457
The Web Services descriptions such as DAML-S/OWL-S, BPEL4WS and WSMF focusing on the functional aspects of Web Services have limitations for the representation of the conceptual and semantic capabilities of Web Services, although WSMF is based on ontology and can represent the goal of Web Services. This paper proposes the new description formalism based on the competence ontology that can represent both functional and semantic aspects of Web Services. This paper also presents the integration and the composition of Web Services by means of Data Mediator(D-Mediator) and Control Mediator(C-Mediator) to mediate compositional in compatibility between heterogeneous Web Services.
Dynamic Web Information Predictive System Using Ensemble Support Vector Machine
Park, Chang-Hee ; Yoon, Kyung-Bae ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 465~470
DOI : 10.3745/KIPSTB.2004.11B.4.465
Web Information Predictive Systems have the restriction such as they need users profiles and visible feedback information for obtaining the necessary information. For overcoming this restrict, this study designed and implemented Dynamic Web Information Predictive System using Ensemble Support Vector Machine to be able to predict the web information and provide the relevant information every user needs most by click stream data and user feedback information, which have some clues based on the data. The result of performance test using Dynamic Web Information Predictive System using Ensemble Support Vector Machine against the existing Web Information Predictive System has preyed that this study s method is an excellence solution.
Dynamic Web Recommendation Method Using Hybrid SOM
Yoon, Kyung-Bae ; Park, Chang-Hee ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 471~476
DOI : 10.3745/KIPSTB.2004.11B.4.471
Recently, provides information which is most necessary to the user the research against the web information recommendation system for the Internet shopping mall is actively being advanced. the back which it will drive in the object. In that Dynamic Web Recommendation Method Using SOM (Self-Organizing Feature Maps) has the advantages of speedy execution and simplicity but has the weak points such as the lack of explanation on models and fired weight values for each node of the output layer on the established model. The method proposed in this study solves the lack of explanation using the Bayesian reasoning method. It does not give fixed weight values for each node of the output layer. Instead, the distribution includes weight using Hybrid SOM. This study designs and implements Dynamic Web Recommendation Method Using Hybrid SOM. The result of the existing Web Information recommendation methods has proved that this study`s method is an excellent solution.
Learning Multidimensional Sequential Patterns Using Hellinger Entropy Function
Lee, Chang-Hwan ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 477~484
DOI : 10.3745/KIPSTB.2004.11B.4.477
The technique of sequential pattern mining means generating a set of inter-transaction patterns residing in time-dependent data. This paper proposes a new method for generating sequential patterns with the use of Hellinger measure. While the current methods are generating single dimensional sequential patterns within a single attribute, the proposed method is able to detect multi-dimensional patterns among different attributes. A number of heuristics, based on the characteristics of Hellinger measure, are proposed to reduce the computational complexity of the sequential pattern systems. Some experimental results are presented.
Fuzzy Clustering Model using Principal Components Analysis and Naive Bayesian Classifier
Jun, Sung-Hae ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 485~490
DOI : 10.3745/KIPSTB.2004.11B.4.485
In data representation, the clustering performs a grouping process which combines given data into some similar clusters. The various similarity measures have been used in many researches. But, the validity of clustering results is subjective and ambiguous, because of difficulty and shortage about objective criterion of clustering. The fuzzy clustering provides a good method for subjective clustering problems. It performs clustering through the similarity matrix which has fuzzy membership value for assigning each object. In this paper, for objective fuzzy clustering, the clustering algorithm which joins principal components analysis as a dimension reduction model with bayesian learning as a statistical learning theory. For performance evaluation of proposed algorithm, Iris and Glass identification data from UCI Machine Learning repository are used. The experimental results shows a happy outcome of proposed model.
Ontology Construction and Its Application to Disambiguate Word Senses
Kang, Sin-Jae ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 491~500
DOI : 10.3745/KIPSTB.2004.11B.4.491
This paper presents an ontology construction method using various computational language resources, and an ontology-based word sense disambiguation method. In order to acquire a reasonably practical ontology the Kadokawa thesaurus is extended by inserting additional semantic relations into its hierarchy, which are classified as case relations and other semantic relations. To apply the ontology to disambiguate word senses, we apply the previously-secured dictionary information to select the correct senses of some ambiguous words with high precision, and then use the ontology to disambiguate the remaining ambiguous words. The mutual information between concepts in the ontology was calculated before using the ontology as knowledge for disambiguating word senses. If mutual information is regarded as a weight between ontology concepts, the ontology can be treated as a graph with weighted edges, and then we locate the weighted path from one concept to the other concept. In our practical machine translation system, our word sense disambiguation method achieved a 9% improvement over methods which do not use ontology for Korean translation.
Performance Improvement by a Virtual Documents Technique in Text Categorization
Lee, Kyung-Soon ; An, Dong-Un ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 501~508
DOI : 10.3745/KIPSTB.2004.11B.4.501
This paper proposes a virtual relevant document technique in the teaming phase for text categorization. The method uses a simple transformation of relevant documents, i.e. making virtual documents by combining document pairs in the training set. The virtual document produced by this method has the enriched term vector space, with greater weights for the terms that co-occur in two relevant documents. The experimental results showed a significant improvement over the baseline, which proves the usefulness of the proposed method: 71% improvement on TREC-11 filtering test collection and 11% improvement on Routers-21578 test set for the topics with less than 100 relevant documents in the micro average F1. The result analysis indicates that the addition of virtual relevant documents contributes to the steady improvement of the performance.
Semantic Image Retrieval Using Color Distribution and Similarity Measurement in WordNet
Choi, Jun-Ho ; Cho, Mi-Young ; Kim, Pan-Koo ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 509~516
DOI : 10.3745/KIPSTB.2004.11B.4.509
Semantic interpretation of image is incomplete without some mechanism for understanding semantic content that is not directly visible. For this reason, human assisted content-annotation through natural language is an attachment of textual description to image. However, keyword-based retrieval is in the level of syntactic pattern matching. In other words, dissimilarity computation among terms is usually done by using string matching not concept matching. In this paper, we propose a method for computerized semantic similarity calculation In WordNet space. We consider the edge, depth, link type and density as well as existence of common ancestors. Also, we have introduced method that applied similarity measurement on semantic image retrieval. To combine wi#h the low level features, we use the spatial color distribution model. When tested on a image set of Microsoft`s `Design Gallery Line`, proposed method outperforms other approach.
An Implementation of Interactive Voice Recognition Stock Trading System Using VoiceXML
Cho, Chang-Su ; Shin, Jeong-Hoon ; Hong, Kwang-Seok ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 517~526
DOI : 10.3745/KIPSTB.2004.11B.4.517
In this paper, we implemented practical application service using VoiceXML. Developers can utilize the advantages of using VoiceXML such as reducing development time and sharing contents between applications. Up to now, speech related services were developed using APIs and programming languages such as C/C++ or exclusive developing tools, which methods depend on system architectures. For this reasons, reuse of contents and resources was very difficult. If developers want to change scenarios of the application services or change platforms, they have to edit and recompile their program sources. To solve these problems, nowadays, companies develop their applications using VoiceXML. But, there`s poor grip of actual problems can be occurred when they use VoiceXML. To overcome these problems, we implemented stock trading system using VoiceXML. We found out problems which occurred during developing services. We proposed solutions to these problems And, we analyzed strong points and weak points of applications using suggested system.
TheReviser : A Gesture-based Editing System on a Digital Desk
Jung, Kee-Chul ; Kang, Hyun ;
The KIPS Transactions:PartB, volume 11B, issue 4, 2004, Pages 527~536
DOI : 10.3745/KIPSTB.2004.11B.4.527
TheReviser is a digital document revision application on a projection display, which allows us to interact a digital document with the same gestures used for paper documents revision. To enable these interactions, TheReviser should detect foreground objects such as hands or pens on a projection display, and should spot and recognize gesture commands from continuous movements of a user. To detect foreground objects from a complex background in various lighting conditions, we perform geometry and color calibration between a captured image and a frame buffer image. TheReviser uses an HMM-based gesture recognition method Experimental results show that the proposed application recognizes user`s gestures on average 93.22% in test gesture sequences.