Go to the main menu
Skip to content
Go to bottom
REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
> Journal Vol & Issue
The KIPS Transactions:PartB
Journal Basic Information
Journal DOI :
Korea Information Processing Society
Editor in Chief :
Volume & Issues
Volume 16B, Issue 6 - Dec 2009
Volume 16B, Issue 5 - Oct 2009
Volume 16B, Issue 4 - Aug 2009
Volume 16B, Issue 3 - Jun 2009
Volume 16B, Issue 2 - Apr 2009
Volume 16B, Issue 1 - Feb 2009
Selecting the target year
Region Segmentation from MR Brain Image Using an Ant Colony Optimization Algorithm
Lee, Myung-Eun ; Kim, Soo-Hyung ; Lim, Jun-Sik ;
The KIPS Transactions:PartB, volume 16B, issue 3, 2009, Pages 195~202
DOI : 10.3745/KIPSTB.2009.16-B.3.195
In this paper, we propose the regions segmentation method of the white matter and the gray matter for brain MR image by using the ant colony optimization algorithm. Ant Colony Optimization (ACO) is a new meta heuristics algorithm to solve hard combinatorial optimization problem. This algorithm finds the expected pixel for image as the real ant finds the food from nest to food source. Then ants deposit pheromone on the pixels, and the pheromone will affect the motion of next ants. At each iteration step, ants will change their positions in the image according to the transition rule. Finally, we can obtain the segmentation results through analyzing the pheromone distribution in the image. We compared the proposed method with other threshold methods, viz. the Otsu` method, the genetic algorithm, the fuzzy method, and the original ant colony optimization algorithm. From comparison results, the proposed method is more exact than other threshold methods for the segmentation of specific region structures in MR brain image.
A Study on Gaze Tracking Based on Pupil Movement, Corneal Specular Reflections and Kalman Filter
Park, Kang-Ryoung ; Ko, You-Jin ; Lee, Eui-Chul ;
The KIPS Transactions:PartB, volume 16B, issue 3, 2009, Pages 203~214
DOI : 10.3745/KIPSTB.2009.16-B.3.203
In this paper, we could simply compute the user`s gaze position based on 2D relations between the pupil center and four corneal specular reflections formed by four IR-illuminators attached on each corner of a monitor, without considering the complex 3D relations among the camera, the monitor, and the pupil coordinates. Therefore, the objectives of our paper are to detect the pupil center and four corneal specular reflections exactly and to compensate for error factors which affect the gaze accuracy. In our method, we compensated for the kappa error between the calculated gaze position through the pupil center and actual gaze vector. We performed one time user calibration to compensate when the system started. Also, we robustly detected four corneal specular reflections that were important to calculate gaze position based on Kalman filter irrespective of the abrupt change of eye movement. Experimental results showed that the gaze detection error was about 1.0 degrees though there was the abrupt change of eye movement.
A Study of Virtual Colored Overlay for Dyslexics
Jang, Young-Gun ; Choi, Hoon-Il ; Yeon, Che-Yong ;
The KIPS Transactions:PartB, volume 16B, issue 3, 2009, Pages 215~224
DOI : 10.3745/KIPSTB.2009.16-B.3.215
A film colored overlay has been used as an assistive device for dyslexics, Recently, several virtual colored overlays which can be used in computer were developed. But existing virtual overlays have some drawbacks which have limited colors and limited control capability over overlapped window by the overlays. Limited colors may prevent optimum color selection and limited control capability can obstruct to transfer keyboard and mouse operation to the overlapped window. In this paper, we implemented an overlay function which controls an overlapped window under the overlay window by using keyboard hooking and tray icon. We propose a method to determine the source color of a virtual overlays by estimating alpha value of alpha blending algorithm through measurement of the chromaticity and transmissivity of film overlays and implemented all colors which we can produce colors by using Intuitive Overlays. Test results of the developed virtual overlay show that all mentioned drawbacks of existing virtual overlays were eliminated. Therefore we can employ a result of WRRT to use the developed overlays.
WordNet-Based Category Utility Approach for Author Name Disambiguation
Kim, Je-Min ; Park, Young-Tack ;
The KIPS Transactions:PartB, volume 16B, issue 3, 2009, Pages 225~232
DOI : 10.3745/KIPSTB.2009.16-B.3.225
Author name disambiguation is essential for improving performance of document indexing, retrieval, and web search. Author name disambiguation resolves the conflict when multiple authors share the same name label. This paper introduces a novel approach which exploits ontologies and WordNet-based category utility for author name disambiguation. Our method utilizes author knowledge in the form of populated ontology that uses various types of properties: titles, abstracts and co-authors of papers and authors` affiliation. Author ontology has been constructed in the artificial intelligence and semantic web areas semi-automatically using OWL API and heuristics. Author name disambiguation determines the correct author from various candidate authors in the populated author ontology. Candidate authors are evaluated using proposed WordNet-based category utility to resolve disambiguation. Category utility is a tradeoff between intra-class similarity and inter-class dissimilarity of author instances, where author instances are described in terms of attribute-value pairs. WordNet-based category utility has been proposed to exploit concept information in WordNet for semantic analysis for disambiguation. Experiments using the WordNet-based category utility increase the number of disambiguation by about 10% compared with that of category utility, and increase the overall amount of accuracy by around 98%.
Document Classification of Small Size Documents Using Extended Relief-F Algorithm
Park, Heum ;
The KIPS Transactions:PartB, volume 16B, issue 3, 2009, Pages 233~238
DOI : 10.3745/KIPSTB.2009.16-B.3.233
This paper presents an approach to the classifications of small size document using the instance-based feature filtering Relief-F algorithm. In the document classifications, we have not always good classification performances of small size document included a few features. Because total number of feature in the document set is large, but feature count of each document is very small relatively, so the similarities between documents are very low when we use general assessment of similarity and classifiers. Specially, in the cases of the classification of web document in the directory service and the classification of the sectors that cannot connect with the original file after recovery hard-disk, we have not good classification performances. Thus, we propose the Extended Relief-F(ERelief-F) algorithm using instance-based feature filtering algorithm Relief-F to solve problems of Relief-F as preprocess of classification. For the performance comparison, we tested information gain, odds ratio and Relief-F for feature filtering and getting those feature values, and used kNN and SVM classifiers. In the experimental results, the Extended Relief-F(ERelief-F) algorithm, compared with the others, performed best for all of the datasets and reduced many irrelevant features from document sets.
Recognition of Korean Text in Outdoor Signboard Images Using Directional Feature and Fisher Measure
Lim, Jun-Sik ; Kim, Soo-Hyung ; Lee, Guee-Sang ; Yang, Hyung-Jung ; Lee, Myung-Eun ;
The KIPS Transactions:PartB, volume 16B, issue 3, 2009, Pages 239~246
DOI : 10.3745/KIPSTB.2009.16-B.3.239
In this paper, we propose a Korean character recognition method from outboard signboard images. We have chosen 808 classes of Korean characters by an analysis of frequencies of appearance in a dictionary of signboard names. The proposed method mainly consists of three steps: feature extraction, rough classification, and coarse classification. The first step is to extract a nonlinear directional segments feature, which is immune to the distortion of character shapes. The second step computes an ordered set of 10 recognition candidates using a minimum distance classifier. The last step reorders the recognition candidates using a Fisher discriminant measure. As experimental results, the recognition accuracy is 80.45% for the first choice, and 93.51% for the top five choices.
Resampling Feedback Documents Using Overlapping Clusters
Lee, Kyung-Soon ;
The KIPS Transactions:PartB, volume 16B, issue 3, 2009, Pages 247~256
DOI : 10.3745/KIPSTB.2009.16-B.3.247
Typical pseudo-relevance feedback methods assume the top-retrieved documents are relevant and use these pseudo-relevant documents to expand terms. The initial retrieval set can, however, contain a great deal of noise. In this paper, we present a cluster-based resampling method to select better pseudo-relevant documents based on the relevance model. The main idea is to use document clusters to find dominant documents for the initial retrieval set, and to repeatedly feed the documents to emphasize the core topics of a query. Experimental results on large-scale web TREC collections show significant improvements over the relevance model. For justification of the resampling approach, we examine relevance density of feedback documents. The resampling approach shows higher relevance density than the baseline relevance model on all collections, resulting in better retrieval accuracy in pseudo-relevance feedback. This result indicates that the proposed method is effective for pseudo-relevance feedback.