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 13B, Issue 7 - Dec 2006
Volume 13B, Issue 6 - Dec 2006
Volume 13B, Issue 5 - Oct 2006
Volume 13B, Issue 4 - Aug 2006
Volume 13B, Issue 3 - Jun 2006
Volume 13B, Issue 2 - Apr 2006
Volume 13B, Issue 1 - Feb 2006
Selecting the target year
Edge-Enhanced Error Diffusion Halftoning using Local mean and Spatial Activity
Kwak Nae-Joung ; Kwon Dong-Jin ; Kim Young-Gil ; Ahn Jae-Hyeong ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 77~82
DOI : 10.3745/KIPSTB.2006.13B.2.077
Digital halftoning is the technique to obtain a bilevel-toned image from continuous-toned image. Among halftoning methods, the error diffusion method gives better subjective quality than other halftoning ones. But it also makes edges of objects blurred. To overcome the defect, we proposes the modified error diffusion to enhance the edges using the property that human vision perceives the local average luminance and doesn`t perceive a little variation of the spatial variation. The proposed method computes a spatialactivity, which is the difference between a pixel luminance and the average of its
neighborhood pixels` Iuminance weighted according to the spatial positioning. The system also usesof edge enhancement (IEE), which is computed from the normalized spatial activitymultiplied by the average luminance. The IEE is added to the quantizer`s input pixel and feeds into the halftoning quantizer. The quantizer produces the halftone image having the enhanced edge. The computer experimental results show that the proposed method produces clearer bilevel-toned images than conventional methodsand the edge of objects is preserved well. Also the performance of the preposed method is improved, compared with that of the conventional method by measuring the edge correlation and the local average accordance at some ranges of viewing distance.
A Study on Digital Image Processing Algorithm for Area Measurement of an Object Image by the Hierarchical Angle-Distance Graphs
Kim Woong-Ki ; Ra Sung-Woong ; Lee Jung-Won ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 83~88
DOI : 10.3745/KIPSTB.2006.13B.2.083
Digital image processing algorithm was proposed to measure the area inside of an object image using angle-distance graph used to analyze the pattern of an object in the digital image processing techniques. The first angle-distance graph is generated from a point inside of an object area. The second angle-distance graphs are generated for the areas missed in the first graph by extracting the positions with large gradient in the first angle-distance graph. The order of the graph increases according to the complexity of an object pattern. Size of the area inside of an object boundary is measured by integrating square of distance multiplied by angle for each area from the hierarchical angie-distance graphs.
Character Segmentation on Printed Korean Document Images Using a Simplification of Projection Profiles
Park Sang-Cheol ; Kim Soo-Hyung ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 89~96
DOI : 10.3745/KIPSTB.2006.13B.2.089
In this paper, we propose two approaches for the character segmentation on Korean document images. One is an improved version of a projection profile-based algorithm. It involves estimating the number of characters, obtaining the split points and then searching for each character`s boundary, and selecting the best segmentation result. The other is developed for low quality document images where adjacent characters are connected. In this case, parts of the projection profile are cut to resolve the connection between the characters. This is called
-cut. Afterwards, the revised former segmentation procedure is conducted. The two approaches have been tested with 43,572 low-quality Korean word images punted in various font styles. The segmentation accuracies of the former and the latter are 91.81% and 99.57%, respectively. This result shows that the proposed algorithm using a
-cut is effective for low-quality Korean document images.
Face Feature Extraction for Child Ocular Inspection and Diagnosis of Colics by Crying Analysis
Cho Dong-Uk ; Kim Bong-Hyun ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 97~104
DOI : 10.3745/KIPSTB.2006.13B.2.097
There is no method to control for the child efficiently when disease happens who cannot be able to express his symptoms. Therefore, doctor`s diagnosis depends on inquiring from child`s patients, that leads to wrong diagnosis result. For this, in this paper, we would like to develop child ocular inspection, auscultation diagnosis instruments, using Oriental medicine principle that living body signal of five organs and six hallow organs which reflects patients face and voice We would like to get more accurate diagnosis result for child`s symptoms from doctor`s intuition on the basis of diagnostic sight visualization, objectification, quantization itself. This paper develops color revision, YCbCr application, and face color selection and five sensory organs and nose or apex extraction method etc, in child ocular inspection by first work achievement sequence among the whole development systems. Also, in occasion of child auscultation, crying characteristics of colics through pitch, intensity and formant analysis is numerized and objectifies doctor`s intuition through this. Finally, experiments are performed to verify the effectiveness of the proposed methods.
Metamorphosis Hierarchical Motion Vector Estimation Algorithm for Multidimensional Image System
Kim Jeong-Woong ; Yang Hae-Sool ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 105~114
DOI : 10.3745/KIPSTB.2006.13B.2.105
In ubiquitous environment where various kinds of computers are embedded in persons, objects and environment and they are interconnected and can be used in my place as necessary, different types of data need to be exchanged between heterogeneous machines through home network. In the environment, the efficient processing, transmission and monitoring of image data are essential technologies. We need to make research not only on traditional image processing such as spatial and visual resolution, color expression and methods of measuring image quality but also on transmission rate on home network that has a limited bandwidth. The present study proposes a new motion vector estimation algorithm for transmitting, processing and controlling image data, which is the core part of contents in home network situation and, using algorithm, implements a real time monitoring system of multi dimensional images transmitted from multiple cameras. Image data of stereo cameras to be transmitted in different environment in angle, distance, etc. are preprocessed through reduction, magnification, shift or correction, and compressed and sent using the proposed metamorphosis hierarchical motion vector estimation algorithm for the correction of motion. The proposed algorithm adopts advantages and complements disadvantages of existing motion vector estimation algorithms such as whole range search, three stage search and hierarchical search, and estimates efficiently the motion of images with high variation of brightness using an atypical small size macro block. The proposed metamorphosis hierarchical motion vector estimation algorithm and implemented image systems can be utilized in various ways in ubiquitous environment.
Contour-Based Partial Object Recognition Of Elliptical Objects Using Symmetry
Cho June-Suh ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 115~120
DOI : 10.3745/KIPSTB.2006.13B.2.115
In This Paper, We Propose The Method To Reconstruct And Estimate Partially Occluded Elliptical Objects In Images From Overlapping And Cutting. We Present The Robust Method For Recognizing Partially Occluded Objects Based On Symmetry Properties, Which Is Based On The Contours Of Elliptical Objects. A Proposed Method Provides Simple Techniques To Reconstruct Occluded Regions Via A Region Copy Using The Symmetry Axis Within An Object. Based On The Estimated Parameters For Partially Occluded Objects, We Perform Object Recognition On The Classifier. Since A Proposed Method Relies On Reconstruction Of The Object Based On The Symmetry Properties Rather Than Statistical Estimates, It Has Proven To Be Remarkably Robust In Recognizing Partially Occluded Objects In The Presence Of Scale Changes, Object Pose, And Rotated Objects With Occlusion, Even Though h Proposed Method Has Minor Limitations Of Object Poses.
The Effectiveness of High-level Text Features in SOM-based Web Image Clustering
Cho Soo-Sun ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 121~126
DOI : 10.3745/KIPSTB.2006.13B.2.121
In this paper, we propose an approach to increase the power of clustering Web images by using high-level semantic features from text information relevant to Web images as well as low-level visual features of image itself. These high-level text features can be obtained from image URLs and file names, page titles, hyperlinks, and surrounding text. As a clustering engine, self-organizing map (SOM) proposed by Kohonen is used. In the SOM-based clustering using high-level text features and low-level visual features, the 200 images from 10 categories are divided in some suitable clusters effectively. For the evaluation of clustering powers, we propose simple but novel measures indicating the degrees of scattering images from the same category, and degrees of accumulation of the same category images. From the experiment results, we find that the high-level text features are more useful in SOM-based Web image clustering.
A New Incremental Instance-Based Learning Using Recursive Partitioning
Han Jin-Chul ; Kim Sang-Kwi ; Yoon Chung-Hwa ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 127~132
DOI : 10.3745/KIPSTB.2006.13B.2.127
K-NN (k-Nearest Neighbors), which is a well-known instance-based learning algorithm, simply stores entire training patterns in memory, and uses a distance function to classify a test pattern. K-NN is proven to show satisfactory performance, but it is notorious formemory usage and lengthy computation. Various studies have been found in the literature in order to minimize memory usage and computation time, and NGE (Nested Generalized Exemplar) theory is one of them. In this paper, we propose RPA (Recursive Partition Averaging) and IRPA (Incremental RPA) which is an incremental version of RPA. RPA partitions the entire pattern space recursively, and generates representatives from each partition. Also, due to the fact that RPA is prone to produce excessive number of partitions as the number of features in a pattern increases, we present IRPA which reduces the number of representative patterns by processing the training set in an incremental manner. Our proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory.
Genetic Algorithm Based Attribute Value Taxonomy Generation for Learning Classifiers with Missing Data
Joo Jin-U ; Yang Ji-Hoon ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 133~138
DOI : 10.3745/KIPSTB.2006.13B.2.133
Learning with Attribute Value Taxonomies (AVT) has shown that it is possible to construct accurate, compact and robust classifiers from a partially missing dataset (dataset that contains attribute values specified with different level of precision). Yet, in many cases AVTs are generated from experts or people with specialized knowledge in their domain. Unfortunately these user-provided AVTs can be time-consuming to construct and misguided during the AVT building process. Moreover experts are occasionally unavailable to provide an AVT for a particular domain. Against these backgrounds, this paper introduces an AVT generating method called GA-AVT-Learner, which finds a near optimal AVT with a given training dataset using a genetic algorithm. This paper conducted experiments generating AVTs through GA-AVT-Learner with a variety of real world datasets. We compared these AVTs with other types of AVTs such as HAC-AVTs and user-provided AVTs. Through the experiments we have proved that GA-AVT-Learner provides AVTs that yield more accurate and compact classifiers and improve performance in learning missing data.
Ontology-based Semantic Assembly Modeling for Collaborative Product Design
Yang Hyung-Jeong ; Kim Kyung-Yun ; Kim Soo-Hyung ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 139~148
DOI : 10.3745/KIPSTB.2006.13B.2.139
In the collaborative product design environment, the communication between designers is important to capture design intents and to share a common view among the different but semantically similar terms. The Semantic Web supports integrated and uniform access to information sources and services as well as intelligent applications by the explicit representation of the semantics buried in ontology. Ontologies provide a source of shared and precisely defined terms that can be used to describe web resources and improve their accessibility to automated processes. Therefore, employing ontologies on assembly modeling makes assembly knowledge accurate and machine interpretable. In this paper, we propose a framework of semantic assembly modeling using ontologies to share design information. An assembly modeling ontology plays as a formal, explicit specification of a shared conceptualization of assembly design modeling. In this paper, implicit assembly constraints are explicitly represented using OWL (Web Ontology Language) and SWRL (Semantic Web Rule Language). The assembly ontology also captures design rationale including joint intent and spatial relationships.
Document Summarization Based on Sentence Clustering Using Graph Division
Lee Il-Joo ; Kim Min-Koo ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 149~154
DOI : 10.3745/KIPSTB.2006.13B.2.149
The main purpose of document summarization is to reduce the complexity of documents that are consisted of sub-themes. Also it is to create summarization which includes the sub-themes. This paper proposes a summarization system which could extract any salient sentences in accordance with sub-themes by using graph division. A document can be represented in graphs by using chosen representative terms through term relativity analysis based on co-occurrence information. This graph, then, is subdivided to represent sub-themes through connected information. The divided graphs are types of sentence clustering which shows a close relationship. When salient sentences are extracted from the divided graphs, summarization consisted of core elements of sentences from the sub-themes can be produced. As a result, the summarization quality will be improved.
Automatic Korean to English Cross Language Keyword Assignment Using MeSH Thesaurus
Lee Jae-Sung ; Kim Mi-Suk ; Oh Yong-Soon ; Lee Young-Sung ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 155~162
DOI : 10.3745/KIPSTB.2006.13B.2.155
The medical thesaurus, MeSH (Medical Subject Heading), has been used as a controlled vocabulary thesaurus for English medical paper indexing for a long time. In this paper, we propose an automatic cross language keyword assignment method, which assigns English MeSH index terms to the abstract of a Korean medical paper. We compare the performance with the indexing performance of human indexers and the authors. The procedure of index term assignment is that first extracting Korean MeSH terms from text, changing these terms into the corresponding English MeSH terms, and calculating the importance of the terms to find the highest rank terms as the keywords. For the process, an effective method to solve spacing variants problem is proposed. Experiment showed that the method solved the spacing variant problem and reduced the thesaurus space by about 42%. And the experiment also showed that the performance of automatic keyword assignment is much less than that of human indexers but is as good as that of authors.
Performance Improvement of Spam Filtering Using User Actions
Kim Jae-Hoon ; Kim Kang-Min ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 163~170
DOI : 10.3745/KIPSTB.2006.13B.2.163
With rapidly developing Internet applications, an e-mail has been considered as one of the most popular methods for exchanging information. The e-mail, however, has a serious problem that users ran receive a lot of unwanted e-mails, what we called, spam mails, which cause big problems economically as well as socially. In order to block and filter out the spam mails, many researchers and companies have performed many sorts of research on spam filtering. In general, users of e-mail have different criteria on deciding if an e-mail is spam or not. Furthermore, in e-mail client systems, users do different actions according to a spam mail or not. In this paper, we propose a mail filtering system using such user actions. The proposed system consists of two steps: One is an action inference step to draw user actions from an e-mail and the other is a mail classification step to decide if the e-mail is spam or not. All the two steps use incremental learning, of which an algorithm is IB2 of TiMBL. To evaluate the proposed system, we collect 12,000 mails of 12 persons. The accuracy is
according to each person. The proposed system outperforms, at about 14% on the average, a system that does not use any information about user actions.
Learning Rules for Identifying Hypernyms in Machine Readable Dictionaries
Choi Seon-Hwa ; Park Hyuk-Ro ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 171~178
DOI : 10.3745/KIPSTB.2006.13B.2.171
Most approaches for extracting hypernyms of a noun from its definitions in an MRD rely on lexical patterns compiled by human experts. Not only these approaches require high cost for compiling lexical patterns but also it is very difficult for human experts to compile a set of lexical patterns with a broad-coverage because in natural languages there are various expressions which represent same concept. To alleviate these problems, this paper proposes a new method for extracting hypernyms of a noun from its definitions in an MRD. In proposed approach, we use only syntactic (part-of-speech) patterns instead of lexical patterns in identifying hypernyms to reduce the number of patterns with keeping their coverage broad. Our experiment has shown that the classification accuracy of the proposed method is 92.37% which is significantly much better than that of previous approaches.
Mobile Terminal-Based User Interface for Intelligent Robots
Kim Gi-Oh ; Xuan Pham Dai ; Park Ji-Hwan ; Hong Soon-Hyuk ; Jeon Jae-Wook ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 179~186
DOI : 10.3745/KIPSTB.2006.13B.2.179
A user interface that connects a user to intelligent robots needs to be designed for executing them efficiently. In this paper, it is analyzed how to organize a mobile terminal based user interface according to the function and level of autonomy of intelligent robots and the user interface of PDA (Personal Digital Assistant) and smart phone is developed for controlling intelligent robots remotely. In the image-based user interface, a user can see the motion of a robot directly and control the robot. In the map-based interface, the quantity of transmission information is reduced and therefore a user can control the robot with a small delay of transmission time.
An Efficient Generation of Walking and Running Motion on Various Terrains
Song Mi-Young ; Cho Hyung-Je ;
The KIPS Transactions:PartB, volume 13B, issue 2, 2006, Pages 187~196
DOI : 10.3745/KIPSTB.2006.13B.2.187
In 3D animation most people adjust the moving motion of their characters on various terrains by using motion data acquired with the motion capture equipment. The motion data can be used to present real human motions naturally, but the data must be captured again to apply to the different terrains from those given at acquiring mode. In addition, there would be a difficulty when applying the data to other characters, in that case the motion data must be captured newly or the existing motion data must be heavily edited manually. In this paper we propose a unified method to generate human motions of walking and running for various terrains such as flat plane, inclined plane, stairway and irregular face. With these methods we are able to generate human motions controlled by the parameters : body height, moving speed, stride, etc. In the proposed methods, the positions and angles of joint can be calculated by using inverse kinematics, and we calculate the trajectory of the swing leg and pelvis according to the cubic spline. With these methods we were presented moving motions using a model of a human body.