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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 15B, Issue 6 - Dec 2008
Volume 15B, Issue 5 - Oct 2008
Volume 15B, Issue 4 - Aug 2008
Volume 15B, Issue 3 - Jun 2008
Volume 15B, Issue 2 - Apr 2008
Volume 15B, Issue 1 - Feb 2008
Selecting the target year
A 2-Dimensional Barcode Detection Algorithm based on Block Contrast and Projection
Choi, Young-Kyu ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 259~268
DOI : 10.3745/KIPSTB.2008.15-B.4.259
In an effort to increase the data capacity of one-dimensional symbology, 2D barcodes have been proposed a decade ago. In this paper, we present an effective 2D barcode detection algorithm from gray-level images, especially for the handheld 2D barcode recognition system. To locate the symbol inside the image, a criteria based on the block contrast is adopted, and a gray-scale projection with sub-pixel operation is utilized to segment the symbol precisely from the region of interest(ROI). Finally, the segmented ROI is normalized using the inverse perspective transformation for the following decoding processes. We also introduce the post-processing steps for decoding the QR-code. The proposed method ensures high performances under various lighting/printing conditions and strong perspective deformations. Experiments shows that our method is very robust and efficient in detecting the code area for the various types of 2D barcodes in real time.
A New EDGE-BASED Stereo Correspondence Method for Snake-Based Object Segmentation
Park, Min-Gyu ; Alattar, Ashraf ; Jang, Jong-Whan ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 269~274
DOI : 10.3745/KIPSTB.2008.15-B.4.269
In this paper, we propose a new stereo correspondence method for generating excellent external energy for snake-based object segmentation methods in stereo images. Our method first generates an edge-based disparity map by performing stereo correspondence between multi-level edge maps of the stereo image pair. Only edges of similar strength are considered for matching. To filter the disparity map for edges of the object of interest, the method estimates the object's disparity value by matching the pattern of edges of the region of interest in the left image against candidate patterns in the right image. The filtered edge map is then used to generate external energy for the snake. The proposed method has been tested on two snake models and results show a noticeable enhancement on performance of the snake when compared with other methods.
A Study on Touchless Finger Vein Recognition Robust to the Alignment and Rotation of Finger
Park, Kang-Ryoung ; Jang, Young-Kyoon ; Kang, Byung-Jun ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 275~284
DOI : 10.3745/KIPSTB.2008.15-B.4.275
With increases in recent security requirements, biometric technology such as fingerprints, faces and iris recognitions have been widely used in many applications including door access control, personal authentication for computers, internet banking, automatic teller machines and border-crossing controls. Finger vein recognition uses the unique patterns of finger veins in order to identify individuals at a high level of accuracy. This paper proposes new device and methods for touchless finger vein recognition. This research presents the following five advantages compared to previous works. First, by using a minimal guiding structure for the finger tip, side and the back of finger, we were able to obtain touchless finger vein images without causing much inconvenience to user. Second, by using a hot mirror, which was slanted at the angle of 45 degrees in front of the camera, we were able to reduce the depth of the capturing device. Consequently, it would be possible to use the device in many applications having size limitations such as mobile phones. Third, we used the holistic texture information of the finger veins based on a LBP (Local Binary Pattern) without needing to extract accurate finger vein regions. By using this method, we were able to reduce the effect of non-uniform illumination including shaded and highly saturated areas. Fourth, we enhanced recognition performance by excluding non-finger vein regions. Fifth, when matching the extracted finger vein code with the enrolled one, by using the bit-shift in both the horizontal and vertical directions, we could reduce the authentic variations caused by the translation and rotation of finger. Experimental results showed that the EER (Equal Error Rate) was 0.07423% and the total processing time was 91.4ms.
PCA-SVM Based Vehicle Color Recognition
Park, Sun-Mi ; Kim, Ku-Jin ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 285~292
DOI : 10.3745/KIPSTB.2008.15-B.4.285
Color histograms have been used as feature vectors to characterize the color features of given images, but they have a limitation in efficiency by generating high-dimensional feature vectors. In this paper, we present a method to reduce the dimension of the feature vectors by applying PCA (principal components analysis) to the color histogram of a given vehicle image. With SVM (support vector machine) method, the dimension-reduced feature vectors are used to recognize the colors of vehicles. After reducing the dimension of the feature vector by a factor of 32, the successful recognition rate is reduced only 1.42% compared to the case when we use original feature vectors. Moreover, the computation time for the color recognition is reduced by a factor of 31, so we could recognize the colors efficiently.
A Digital Image Watermarking Using A Bottom-up Attention Module
Cheoi, Kyung-Joo ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 293~300
DOI : 10.3745/KIPSTB.2008.15-B.4.293
This paper takes a bottom-up attention module into consideration for digital image watermarking. A bottom-up attention module is employed to obtain the region of interest, and watermark information is embedded into the obtained region. Previous studies in digital image watermarking have been focused on the signal processing techniques, especially in waveform coding spreading watermarks over the entire target image. However, we notice that the third party's visual attention is usually concentrated on a few regions in an image but not on all of them. These regions are easy to be the target of attacks. If watermark information is inserted into these regions from the beginning, it can be detected with high correlation. Various kinds of images are tested, and the results showed good quality.
Spectrum Feature Analysis of Crying Sounds of Infant Cold and Pneumonia
Kim, Bong-Hyun ; Lee, Se-Hwan ; Cho, Dong-Uk ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 301~306
DOI : 10.3745/KIPSTB.2008.15-B.4.301
Recently, various health care methods for infants have been suggested in the impending era of low birth rate society. We propose, in this context, an early diagnosis method for common infant respiratory diseases. Particularly, the method is regarding infant cold and infant pneumonia. Firstly, sounds of infant crying, only expressing means of infants, among the infant cold group and the infant pneumonia group are compared and examined to find the differences from those among the healthy infant group. For this, the link between infected organs and articulatory organs is investigated. Also, resulting wave forms and frequency bandwidths among each group are compared and analyzed, by using the spectrum for a component voice, to diagnose the infant cold and pneumonia. Finally, the effectiveness of this method is verified through the experiments.
Print-Scan Resilient Curve Watermarking using B-Spline Curve Model and its 2D Mesh-Spectral Transform
Kim, Ji-Young ; Lee, Hae-Yeoun ; Im, Dong-Hyuck ; Ryu, Seung-Jin ; Choi, Jung-Ho ; Lee, Heung-Kyu ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 307~314
DOI : 10.3745/KIPSTB.2008.15-B.4.307
This paper presents a new robust watermarking method for curves that uses informed-detection. To embed watermarks, the presented algorithm parameterizes a curve using the B-spline model and acquires the control points of the B-spline model. For these control points, 2D mesh are created by applying Delaunay triangulation and then the mesh spectral analysis is performed to calculate the mesh spectral coefficients where watermark messages are embedded in a spread spectrum way. The watermarked coefficients are inversely transformed to the coordinates of the control points and the watermarked curve is reconstructed by calculating B-spline model with the control points. To detect the embedded watermark, we apply curve matching algorithm using inflection points of curve. After curve registration, we calculate the difference between the original and watermarked mesh spectral coefficients with the same process for embedding. By calculating correlation coefficients between the detected and candidate watermark, we decide which watermark was embedded. The experimental results prove the proposed scheme is more robust than previous watermarking schemes against print-scan process as well as geometrical distortions.
Service Provider Ranking Based on Visual Media Ontology
Min, Young-Kun ; Lee, Bog-Ju ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 315~322
DOI : 10.3745/KIPSTB.2008.15-B.4.315
It is important to retrieve effectively the visual media such as pictures and video in the internet, especially to the application areas such as electronic art museum, e-commerce, and internet shopping malls. It is also needed in these areas to have content-based or even semantic-based multimedia retrieval instead of simple keyword-based retrieval. In our earlier research, we proposed a semantic-based visual media retrieval framework for the effective retrieval of the visual media from the internet. It uses visual media metadata and ontology based on the web service to achieve the semantic-based retrieval. In this research, there are more than one visual media service providers and one central service broker. As a preliminary step to the visual media data retrieval, a method is proposed to retrieve the service providers effectively. The method uses the structure of the ontology tree to obtain the providers and their rankings. It also uses the size of sub nodes and child nodes in the tree. It measures the rankings of providers more effectively than previous method. The experimental results show the accuracy of the method while keeping compatible speed against the existing method.
A Prediction Model for Complex Diseases using Set Association & Artificial Neural Network
Choi, Hyun-Joo ; Kim, Seung-Hyun ; Wee, Kyu-Bum ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 323~330
DOI : 10.3745/KIPSTB.2008.15-B.4.323
Since complex diseases are caused by interactions of multiple genes, traditional statistical methods are limited in its power to predict the onset of a complex disease. Recently new approaches using machine learning techniques are introduced. Neural nets are a suitable model to find patterns in complex data. When large amount of data are fed into a neural net, however, it takes a long time for learning and finding patterns. In this study we suggest a new model that combines the set association, which is a statistical technique to find important SNPs associated with complex diseases, and neural network. We experiment with SNP data related to asthma to test the effectiveness of our model. Our model shows higher prediction accuracy and shorter execution time than neural net only. We expect our model can be used effectively to predict the onset of other complex diseases.
Performance Improvement of Feature Selection Methods based on Bio-Inspired Algorithms
Yun, Chul-Min ; Yang, Ji-Hoon ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 331~340
DOI : 10.3745/KIPSTB.2008.15-B.4.331
Feature Selection is one of methods to improve the classification accuracy of data in the field of machine learning. Many feature selection algorithms have been proposed and discussed for years. However, the problem of finding the optimal feature subset from full data still remains to be a difficult problem. Bio-inspired algorithms are well-known evolutionary algorithms based on the principles of behavior of organisms, and very useful methods to find the optimal solution in optimization problems. Bio-inspired algorithms are also used in the field of feature selection problems. So in this paper we proposed new improved bio-inspired algorithms for feature selection. We used well-known bio-inspired algorithms, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), to find the optimal subset of features that shows the best performance in classification accuracy. In addition, we modified the bio-inspired algorithms considering the prior importance (prior relevance) of each feature. We chose the mRMR method, which can measure the goodness of single feature, to set the prior importance of each feature. We modified the evolution operators of GA and PSO by using the prior importance of each feature. We verified the performance of the proposed methods by experiment with datasets. Feature selection methods using GA and PSO produced better performances in terms of the classification accuracy. The modified method with the prior importance demonstrated improved performances in terms of the evolution speed and the classification accuracy.
Solving Minimum Weight Triangulation Problem with Genetic Algorithm
Han, Keun-Hee ; Kim, Chan-Soo ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 341~346
DOI : 10.3745/KIPSTB.2008.15-B.4.341
Minimum Weight Triangulation (MWT) problem is an optimization problem searching for the triangulation of a given graph with minimum weight. Like many other graph problems this problem is also known to be NP-hard for general graphs. Several heuristic algorithms have been proposed for this problem including simulated annealing and genetic algorithm. In this paper, we propose a new genetic algorithm called GA-FF and show that the performance of the proposed genetic algorithm outperforms the previous one.
Intelligent Speech Web Considering User Inclination
Kwon, Hyeong-Joon ; Hong, Kwang-Seok ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 347~354
DOI : 10.3745/KIPSTB.2008.15-B.4.347
In this paper, we propose a method for personalizing and intelligence of speech Web. The proposed system records information that was demanded in the past as a transaction, explores association rules from those transactions, and discovers itemsets from frequent requests. This method is to recommend relevant information, based on frequent itemsets, to users who have similar inclinations to previous users. As a result of experimenting and implementation of proposed system for verification, we confirmed that the proposed system can recommend previously frequently requested information as relevant information.
A Multi-level Inverted Index Technique for Structural Document Search
Kim, Jong-Ik ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 355~364
DOI : 10.3745/KIPSTB.2008.15-B.4.355
In general, we can use an inverted index for retrieving element lists from structured documents. An inverted index can retrieve a list of elements that have the same tag name. In this approach, however, the cost of query processing is linear to the length of a path query because all the structural relationships (parent-child and ancestor-descendant) should be resolved by structural join operations. In this paper, we propose an inverted index technique and a novel structural join technique for accelerating XML path query evaluation. Our inverted index can retrieve element lists for path segments in a parent-child relationship. Our structural join technique can handle lists of element pairs while the existing techniques handle lists of elements. We show through experiments that these two proposed techniques are integrated to accelerate evaluation of XML path queries.
Incremental Enrichment of Ontologies through Feature-based Pattern Variations
Lee, Sheen-Mok ; Chang, Du-Seong ; Shin, Ji-Ae ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 365~374
DOI : 10.3745/KIPSTB.2008.15-B.4.365
In this paper, we propose a model to enrich an ontology by incrementally extending the relations through variations of patterns. In order to generalize initial patterns, combinations of features are considered as candidate patterns. The candidate patterns are used to extract relations from Wikipedia, which are sorted out according to reliability based on corpus frequency. Selected patterns then are used to extract relations, while extracted relations are again used to extend the patterns of the relation. Through making variations of patterns in incremental enrichment process, the range of pattern selection is broaden and refined, which can increase coverage and accuracy of relations extracted. In the experiments with single-feature based pattern models, we observe that the features of lexical, headword, and hypernym provide reliable information, while POS and syntactic features provide general information that is useful for enrichment of relations. Based on observations on the feature types that are appropriate for each syntactic unit type, we propose a pattern model based on the composition of features as our ongoing work.
Detection of Protein Subcellular Localization based on Syntactic Dependency Paths
Kim, Mi-Young ;
The KIPS Transactions:PartB, volume 15B, issue 4, 2008, Pages 375~382
DOI : 10.3745/KIPSTB.2008.15-B.4.375
A protein's subcellular localization is considered an essential part of the description of its associated biomolecular phenomena. As the volume of biomolecular reports has increased, there has been a great deal of research on text mining to detect protein subcellular localization information in documents. It has been argued that linguistic information, especially syntactic information, is useful for identifying the subcellular localizations of proteins of interest. However, previous systems for detecting protein subcellular localization information used only shallow syntactic parsers, and showed poor performance. Thus, there remains a need to use a full syntactic parser and to apply deep linguistic knowledge to the analysis of text for protein subcellular localization information. In addition, we have attempted to use semantic information from the WordNet thesaurus. To improve performance in detecting protein subcellular localization information, this paper proposes a three-step method based on a full syntactic dependency parser and WordNet thesaurus. In the first step, we constructed syntactic dependency paths from each protein to its location candidate, and then converted the syntactic dependency paths into dependency trees. In the second step, we retrieved root information of the syntactic dependency trees. In the final step, we extracted syn-semantic patterns of protein subtrees and location subtrees. From the root and subtree nodes, we extracted syntactic category and syntactic direction as syntactic information, and synset offset of the WordNet thesaurus as semantic information. According to the root information and syn-semantic patterns of subtrees from the training data, we extracted (protein, localization) pairs from the test sentences. Even with no biomolecular knowledge, our method showed reasonable performance in experimental results using Medline abstract data. Our proposed method gave an F-measure of 74.53% for training data and 58.90% for test data, significantly outperforming previous methods, by 12-25%.