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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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Digital Watermarking of JPEG Image Based on Human Visual System
Bae, Sung-Ho ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 125~132
DOI : 10.3745/KIPSTB.2004.11B.2.125
In this paper, a watermark inserting method according to the sensitivity of human visual system and minimizing distortion of original DCT coefficients in DCT transform domain is proposed. The proposed method inserts a more robust watermark in the insensitive block of human vision by reordering the blocks according to the human visual system which is appropriate to the JPEG image compression. It also enhances the invisibility and robustness in high compression rate in terms of the watermark inserting method within the block which minimizes distortions of original DCT coefficients. The computer simulation results show that the proposed method maintains high image quality and good robustness in high compression rate compared with conventional watermarking method.
3D Reconstruction System of Teeth for Dental Simulation
Heo, Hoon ; Choi, Won-Jun ; Chae, Ok-Sam ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 133~140
DOI : 10.3745/KIPSTB.2004.11B.2.133
Recently, the dental information systems were rapidly developed in order to store and process the data of patients. But, these systems should serve a doctor a good quality information against disease for diagnostic and surgery purpose so as to success in this field. This function of the system it important to persuade patients to undergo proper surgical operation they needed. Hence, 3D teeth model capable of simulating the dental surgery and treatment is necessary Teeth manipulation of dentistry is performed on individual tooth in dental clinic. io, 3D teeth reconstruction system should have the techniques of segmentation and 3D reconstruction adequate for individual tooth. In this paper, we propose the techniques of adaptive optimal segmentation to segment the individual area of tooth, and reconstruction method of tooth based on contour-based method. Each tooth can be segmented from neighboring teeth and alveolar bone in CT images using adaptive optimal threshold computed differently on tooth. Reconstruction of individual tooth using results of segmentation can be manipulated according to user`s input and make the simulation of dental surgery and treatment possible.
Evaluation of Digital Elevation Models by Interpreting Correlations
Lee, Seung-Woo ; Oh, Hae-Seok ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 141~148
DOI : 10.3745/KIPSTB.2004.11B.2.141
The ground positions and elevations information called DEMs(Digital Elevation Models) which are extracted from the stereo aerial photographs and/or satellite images using image matching method have the natural errors caused by variant environments. This study suggests the method to evaluate DEMs using correlation values between the reference and the target DEMs. This would be strongly helpful for experts to correct these errors. To evaluate the whole area of DEMs in the horizontal and vertical errors, the target cell is matched for each reference cell using the correlation values of these two cells. When the target cell is matched for each reference cell, horizontal and vertical error was calculated so as to help experts to recognize a certain area of DEMs which should be corrected and edited. If the correlation value is low and tile difference in height is high, the target cell will be candidated as changed or corrupted cell. When the area is clustered with those candidated cells, that area will be regarded as changed or corrupted area to be corrected and edited. Using this method, the evaluation for all DEM cells is practicable, the horizontal errors as well as vertical errors is calculable and the changed or corrupted area can be detected more efficiently.
Segmentation and Recognition of Traffic Signs using Shape Information and Edge Image in Real Image
Kwak, Hyun-Wook ; Oh,Jun-Taek ; Kim, Wook-Hyun ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 149~158
DOI : 10.3745/KIPSTB.2004.11B.2.149
This study proposes a method for segmentation and recognition of traffic signs using shape information and edge image in real image. It first segments traffic sign candidate regions by connected component algorithm from binary images, obtained by utilizing the RGB color ratio of each pixel in the image, and then extracts actual traffic signs based on their symmetries on X- and Y-axes. Histogram equalization is performed for unsegmented candidate regions caused by low contrast in the image. In the recognition stage, it utilizes shape information including projection profiles on X- and Y-axes, moment, and the number of crossings and distance which concentric circular patterns and 8-directional rays from region center intersects with edges of traffic signs. It finally performs recognition by measuring similarity with the templates in the database. It will be shown from several experimental results that the system is robust to environmental factors, such as light and weather condition.
A Study on the Classification for Satellite Images using Hybrid Method
Jeon, Young-Joon ; Kim, Jin-Il ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 159~168
DOI : 10.3745/KIPSTB.2004.11B.2.159
This paper presents hybrid classification method to improve the performance of satellite images classification by combining Bayesian maximum likelihood classifier, ISODATA clustering and fuzzy C-Means algorithm. In this paper, the training data of each class were generated by separating the spectral signature using ISODATA clustering. We can classify according to pixel`s membership grade followed by cluster center of fuzzy C-Means algorithm as the mean value of training data for each class. Bayesian maximum likelihood classifier is performed with prior probability by result of fuzzy C-Means classification. The results shows that proposed method could improve performance of classification method and also perform classification with no concern about spectral signature of the training data. The proposed method Is applied to a Landsat TM satellite image for the verifying test.
Color Collection of LCD Monitor Using High-order Multilayer Neural Network
Jung, Jae-Hoon ; Lee, Dong-Wook ; Ahn, Kang-Sic ; Cho, Seok-Je ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 169~176
DOI : 10.3745/KIPSTB.2004.11B.2.169
This paper presents a new color correction method for color reproduction on LCD-based monitor by means of high-order multilayer neural networks. LCD monitors have nonlinear characteristics from various displaying system components. To overcome these nonlinearities and produce quality image, we need a nonlinear transformer for color coordinate transformation between the LCD monitor coordinates and the input color stimulus values. A high-order multilayer neural network is effectively trained to learn a mapping to determine the required color value of monitors for producing a given color stimulus. From the experimental results, the proposed method is effective in reproducing the color images.
A 3D Wavelet Coding Scheme for Light-weight Video Codec
Lee, Seung-Won ; Kim, Sung-Min ; Park, Seong-Ho ; Chung, Ki-Dong ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 177~186
DOI : 10.3745/KIPSTB.2004.11B.2.177
It is a weak point of the motion estimation technique for video compression that the predicted video encoding algorithm requires higher-order computational complexity. To reduce the computational complexity of encoding algorithms, researchers introduced techniques such as 3D-WT that don`t require motion prediction. One of the weakest points of previous 3D-WT studies is that they require too much memory for encoding and too long delay for decoding. In this paper, we propose a technique called `FS (Fast playable and Scalable) 3D-WT` This technique uses a modified Haar wavelet transform algorithm and employs improved encoding algorithm for lower memory and shorter delay requirement. We have executed some tests to compare performance of FS 3D-WT and 3D-V. FS 3D-WT has exhibited the same high compression rate and the same short processing delay as 3D-V has.
WebPR : A Dynamic Web Page Recommendation Algorithm Based on Mining Frequent Traversal Patterns
Yoon, Sun-Hee ; Kim, Sam-Keun ; Lee, Chang-Hoon ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 187~198
DOI : 10.3745/KIPSTB.2004.11B.2.187
The World-Wide Web is the largest distributed Information space and has grown to encompass diverse information resources. However, although Web is growing exponentially, the individual`s capacity to read and digest contents is essentially fixed. From the view point of Web users, they can be confused by explosion of Web information, by constantly changing Web environments, and by lack of understanding needs of Web users. In these Web environments, mining traversal patterns is an important problem in Web mining with a host of application domains including system design and Information services. Conventional traversal pattern mining systems use the inter-pages association in sessions with only a very restricted mechanism (based on vector or matrix) for generating frequent k-Pagesets. We develop a family of novel algorithms (termed WebPR - Web Page Recommend) for mining frequent traversal patterns and then pageset to recommend. Our algorithms provide Web users with new page views, which Include pagesets to recommend, so that users can effectively traverse its Web site. The main distinguishing factors are both a point consistently spanning schemes applying inter-pages association for mining frequent traversal patterns and a point proposing the most efficient tree model. Our experimentation with two real data sets, including Lady Asiana and KBS media server site, clearly validates that our method outperforms conventional methods.
Hybrid ICA of Fixed-Point Algorithm and Robust Algorithm Using Adaptive Adaptation of Temporal Correlation
Cho, Yong-Hyun ; Oh, Jeung-Eun ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 199~206
DOI : 10.3745/KIPSTB.2004.11B.2.199
This paper proposes a hybrid independent component analysis(ICA) of fixed-point(FP) algorithm and robust algorithm. The FP algorithm is applied for improving the analysis speed and performance, and the robust algorithm is applied for preventing performance degradations by means of very small kurtosis and temporal correlations between components. And the adaptive adaptation of temporal correlations has been proposed for solving limits of the conventional robust algorithm dependent on the maximum time delay. The proposed ICA has been applied to the problems for separating the 4-mixed signals of 500 samples and 10-mixed images of
pixels, respectively. The experimental results show that the proposed ICA has a characteristics of adaptively adapting the maximum time delay, and has a superior separation performances(speed, rate) to conventional FP-ICA and hybrid ICA of heuristic correlation. Especially, the proposed ICA gives the larger degree of improvement as the problem size increases.
Optimization of Stock Trading System based on Multi-Agent Q-Learning Framework
Kim, Yu-Seop ; Lee, Jae-Won ; Lee, Jong-Woo ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 207~212
DOI : 10.3745/KIPSTB.2004.11B.2.207
This paper presents a reinforcement learning framework for stock trading systems. Trading system parameters are optimized by Q-learning algorithm and neural networks are adopted for value approximation. In this framework, cooperative multiple agents are used to efficiently integrate global trend prediction and local trading strategy for obtaining better trading performance. Agents Communicate With Others Sharing training episodes and learned policies, while keeping the overall scheme of conventional Q-learning. Experimental results on KOSPI 200 show that a trading system based on the proposed framework outperforms the market average and makes appreciable profits. Furthermore, in view of risk management, the system is superior to a system trained by supervised learning.
Evolutionary Multi - Objective Optimization Algorithms using Pareto Dominance Rank and Density Weighting
Jang, Su-Hyun ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 213~220
DOI : 10.3745/KIPSTB.2004.11B.2.213
Evolutionary algorithms are well-suited for multi-objective optimization problems involving several. often conflicting objective. Pareto-based evolutionary algorithms, in particular, have shown better performance than other multi-objective evolutionary algorithms in comparison. Recently, pareto-based evolutionary algorithms uses a density information in fitness assignment scheme for generating uniform distributed global pareto optimal front. However, the usage of density information is not Important elements in a whole evolution path but plays an auxiliary role in order to make uniform distribution. In this paper, we propose an evolutionary algorithms for multi-objective optimization which assigns the fitness using pareto dominance rank and density weighting, and thus pareto dominance rank and density have similar influence on the whole evolution path. Furthermore, the experimental results, which applied our method to the six multi-objective optimization problems, show that the proposed algorithms show more promising results.
A Effective Ant Colony Algorithm applied to the Graph Coloring Problem
Ahn, Sang-Huck ; Lee, Seung-Gwan ; Chung, Tae-Choong ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 221~226
DOI : 10.3745/KIPSTB.2004.11B.2.221
Ant Colony System(ACS) Algorithm is new meta-heuristic for hard combinational optimization problem. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. Recently, various methods and solutions are proposed to solve optimal solution of graph coloring problem that assign to color for adjacency node(
) that they has not same color. In this paper introducing ANTCOL Algorithm that is method to solve solution by Ant Colony System algorithm that is not method that it is known well as solution of existent graph coloring problem. After introducing ACS algorithm and Assignment Type Problem, show the wav how to apply ACS to solve ATP And compare graph coloring result and execution time when use existent generating functions(ANT_Random, ANT_LF, ANT_SL, ANT_DSATUR, ANT_RLF method) with ANT_XRLF method that use XRLF that apply Randomize to RLF to solve ANTCOL. Also compare graph coloring result and execution time when use method to add re-search to ANT_XRLF(ANT_XRLF_R) with existent generating functions.
Antecedent Decision Rules of Personal Pronouns for Coreference Resolution
Kang, Seung-Shik ; Yun, Bo-Hyun ; Woo, Chong-Woo ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 227~232
DOI : 10.3745/KIPSTB.2004.11B.2.227
When we extract a representative term from text for information retrieval system or a special information for information retrieval and text milling system, we often need to solve the anaphora resolution problem. The antecedent decision problem of a pronoun is one of the major issues for anaphora resolution. In this paper, we are suggesting a method of deciding an antecedent of the third personal pronouns, such as “he/she/they” to analyze the contents of documents precisely. Generally, the antecedent of the third personal Pronouns seem to be the subject of the current statement or previous statement, and also it occasionally happens more than twice. Based on these characteristics, we have found rules for deciding an antecedent, by investigating a case of being an antecedent from the personal pronouns, which appears in the current statement and the previous statements. Since the heuristic rule differs on the case of the third personal pronouns, we described it as subjective case, objective case, and possessive case based on the case of the pronouns. We collected 300 sentences that include a pronoun from the newspaper articles on political issues. The result of our experiment shows that the recall and precision ratio on deciding the antecedent of the third personal pronouns are 79.0% and 86.8%, respectively.
Performance Improvement by Cluster Analysis in Korean-English and Japanese-English Cross-Language Information Retrieval
Lee, Kyung-Soon ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 233~240
DOI : 10.3745/KIPSTB.2004.11B.2.233
This paper presents a method to implicitly resolve ambiguities using dynamic incremental clustering in Korean-to-English and Japanese-to-English cross-language information retrieval (CLIR). The main objective of this paper shows that document clusters can effectively resolve the ambiguities tremendously increased in translated queries as well as take into account the context of all the terms in a document. In the framework we propose, a query in Korean/Japanese is first translated into English by looking up bilingual dictionaries, then documents are retrieved for the translated query terms based on the vector space retrieval model or the probabilistic retrieval model. For the top-ranked retrieved documents, query-oriented document clusters are incrementally created and the weight of each retrieved document is re-calculated by using the clusters. In the experiment based on TREC test collection, our method achieved 39.41% and 36.79% improvement for translated queries without ambiguity resolution in Korean-to-English CLIR, and 17.89% and 30.46% improvements in Japanese-to-English CLIR, on the vector space retrieval and on the probabilistic retrieval, respectively. Our method achieved 12.30% improvements for all translation queries, compared with blind feedback in Korean-to-English CLIR. These results indicate that cluster analysis help to resolve ambiguity.
Language Model based on VCCV and Test of Smoothing Techniques for Sentence Speech Recognition
Park, Seon-Hee ; Roh, Yong-Wan ; Hong, Kwang-Seok ;
The KIPS Transactions:PartB, volume 11B, issue 2, 2004, Pages 241~246
DOI : 10.3745/KIPSTB.2004.11B.2.241
In this paper, we propose VCCV units as a processing unit of language model and compare them with clauses and morphemes of existing processing units. Clauses and morphemes have many vocabulary and high perplexity. But VCCV units have low perplexity because of the small lexicon and the limited vocabulary. The construction of language models needs an issue of the smoothing. The smoothing technique used to better estimate probabilities when there is an insufficient data to estimate probabilities accurately. This paper made a language model of morphemes, clauses and VCCV units and calculated their perplexity. The perplexity of VCCV units is lower than morphemes and clauses units. We constructed the N-grams of VCCV units with low perplexity and tested the language model using Katz, absolute, modified Kneser-Ney smoothing and so on. In the experiment results, the modified Kneser-Ney smoothing is tested proper smoothing technique for VCCV units.