• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.65-73
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• 2008

The characterization process for the accurate color reproduction in mobile phone with camera and LCD is popular. The camera and LCD characterization, gamut mapping process is necessary to map the camera's input color stimulus, CIEXYZ value, into the LCD's output color stimulus. Each characterization is the process estimating the relation between input and output signals. In case of LCD, because of output device, the output color stimulus for the arbitrary input signal can be measured by spectro-radiometer However, in the camera, as the input device, the characterization is an inaccurate and needs the manual works in the process obtaining the output signal because the input signal can not be generated. Moreover, after gamut mapping process, the noise is increased because the optimized gamma tone curve of camera for the noise is distorted by the characterization. Thus, this paper proposed the system of obtaining the output signal of camera and the method of gamma correction for the noise. The camera's output signal is obtained by RGB values of patches from captured the color chart image. However, besides the illumination, the error for the location of the chart in the viewfinder is generated when many camera modules are captured the chart. The method of correcting the position to correct the error from manual works. The position of camera is estimated by captured image. This process and moving of camera is accomplished repeatedly, and the optimized position can be obtained. Moreover, the lightness curve of camera output is corrected partly to reduce the noise from the characterization process.

• The Journal of the Korea Contents Association
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• v.11 no.1
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• pp.438-447
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• 2011

geoContents have been closely related with personal life since the Google Earth and Street View by Google and the Road View by Daum were introduced. So, Location-based content, which is referred to geoContents, involving geometric spacial information and location-based image information is a sharp rise in demand. A mobile mapping system used in the area of map upgrade and road facility management has been having difficulties in satisfying the demand in the cost and time for obtaining these kinds of contents. This paper addresses geoData acquisition and processing system for producing panoramic images. The system consists of 3 devices: the first device is 3 GPS receivers for acquiring location information which is including position, attitude, orientation, and time. The second is 6 cameras for image information. And the last is to synchronize the both data. The geoData acquired by the proposed system and the method for authoring geoContents which are referred to a panoramic image with position, altitude, and orientation will be used as an effective way for establishing the various location-based content and providing them service area.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.506-512
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• 2000

In this paper, we propose a Fuzzy Classifier System(FCS) makes the classifier system be able to carry out the mapping from continuous inputs to outputs. The FCS is based on the fuzzy controller system combined with machine learning. Therefore the antecedent and consequent of a classifier in FCS are the same as those of a fuzzy rule. In this paper, the FCS modifies input message to fuzzified message and stores those in the message list. The FCS constructs rule-base through matching between messages of message list and classifiers of fuzzy classifier list. The FCS verifies the effectiveness of classifiers using Bucket Brigade algorithm. Also the FCS employs the Genetic Algorithms to generate new rules and modifY rules when performance of the system needs to be improved. Then the FCS finds the set of the effective rules. We will verifY the effectiveness of the poposed FCS by applying it to Autonomous Mobile Robot avoiding the obstacle and reaching the goal.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.5
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• pp.1-10
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• 2000

In this paper, we propose a Fuzzy Classifier System(FCS) makes the classifier system be able to carry out the mapping from continuous inputs to outputs. The FCS is based on the fuzzy controller system combined with machine learning. Therefore the antecedent and consequent of a classifier in FCS are the same as those of a fuzzy rule. In this paper, the FCS modifies input message to fuzzified message and stores those in the message list. The FCS constructs rule-base through matching between messages of message list and classifiers of fuzzy classifier list. The FCS verifies the effectiveness of classifiers using Bucket Brigade algorithm. Also the FCS employs the Genetic Algorithms to generate new rules and modify rules when performance of the system needs to be improved. Then the FCS finds the set of the effective rules. We will verify the effectiveness of the poposed FCS by applying it to Autonomous Mobile Robot avoiding the obstacle and reaching the goal.

• Journal of Environmental Health Sciences
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• v.38 no.5
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• pp.369-379
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• 2012

Objectives: Spatial analysis is useful for understanding complicated causal relationships. This paper focuses trends and appling methods for spatial analysis associated with environmental asbestos exposure. Methods: Literature review and reflection of experience of authors were conducted to know academic background of spatial analysis, appling methods on epidemiology and asbestos exposure. Results: Spatial analysis based on spatial autocorrelation provides a variety of methods through which to conduct mapping, cluster analysis, diffusion, interpolation, and identification. Cause of disease occurrence can be investigated through spatial analysis. Appropriate methods can be applied according to contagiousness and continuity. Spatial analysis for asbestos exposure source is needed to study asbestos related diseases. Although a great amount of research has used spatial analysis to study exposure assessment and distribution of disease occurrence, these studies tend to focus on the construction of a thematic map without different forms of analysis. Recently, spatial analysis has been advanced by merging with web tools, mobile computing, statistical packages, social network analysis, and big data. Conclusions: Because the trend in spatial analysis has evolved from simple marking into a variety of forms of analyses, environmental researchers including asbestos exposure study are required to be aware of recent trends.

• The Journal of Korea Robotics Society
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• v.7 no.1
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• pp.29-34
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• 2012

This paper suggests a new observation model for Extended Kalman Filter based Simultaneous Localization and Mapping (EKF-SLAM). Since the EKF framework linearizes non-linear functions around the current estimate, the conventional line model has large linearization errors when a mobile robot locates faraway from its initial position. On the other hand, the model that we propose yields less linearization error with respect to the landmark position and thus suitable in a large-scale environment. To achieve it, we build up a three-dimensional space by adding a virtual axis to the robot's two-dimensional coordinate system and extract a plane by using a detected line on the two-dimensional space and the virtual axis. Since Jacobian matrix with respect to the landmark position has small value, we can estimate the position of landmarks better than the conventional line model. The simulation results verify that the new model yields less linearization errors than the conventional line model.

• Journal of Korea Multimedia Society
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• v.8 no.5
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• pp.721-728
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• 2005

A virtual machine is a conceptual computer with a logical system configuration, made of software unlike physical systems made of hardware. Virtual machine technology for embedded systems is a requisite software technology for download solutions such as mobile devices, digital TVs, etc. At present, a research of virtual machines for embedded systems named EVM(Embedded Virtual Machine) is in progress. As a part of the research, we define the EFF(Executable File Format) as a file format for embedded systems. We also prove completeness of EFF by structurally mapping class file widely used to EFF.

• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.104-110
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• 2014

Mapping is a fundamental element for robotic services. There are available many types of map data representation such as grid map, metric map, topology map, etc. As more robots are deployed for services, more chances of exchanging map data among the robots emerge and standardization of map data representation (MDR) becomes more valuable. Currently, activities in developing MDR standard are underway in IEEE Robotics and Automation Society. The MDR standard is for a common representation and encoding of the two-dimensional map data used for navigation by mobile robots. The standard focuses on interchange of map data among components and systems, particularly those that may be supplied by different vendors. This paper aims to introduce MDR standard and its application to map merging. We have applied the basic structure of the MDR standard to a grid map and Voronoi graph as a kind of topology map and performed map merging between two different maps. Simulation results show that the proposed MDR is suitable for map data exchange among robots.

• 한국지형공간정보학회:학술대회논문집
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• 2004.10a
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• pp.175-181
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• 2004

우리나라에서는 1995년부터 국가지리정보체계(NGIS)구축 기본계획을 수립하여 건설교통부, 정보통신부, 과학기술부 및 행정자치부 등 범국가적으로 2000년까지 제 1단계 사업을 마쳤으며, 2001년부터 제 2단계 사업을 추진 중에 있다. 하지만 국가지형 및 시설물 등이 하루가 다르게 변화하는 정보화 사회에서 다양한 객체에 대한 위치 및 속성정보의 획득, 저장, 관리, 활용을 위한 신속한 수치지도 수정갱신이 요구된다. 또한 도로시설물을 비롯한 다양한 지형지물정보는 공간정보를 다루는 도시, 교통, 물류, 환경 및 군사 분야 등 다양한 분야에서 의사결정 및 계획에 필수적으로 요구되는 정보이고 이와 같은 정보는 신속하고 정확하게 취득되어야 하며, 경제적이며, 효율적으로 정보를 획득하는 신기술을 적용한 작업방법론이 필요하다. 현재 국내에서도 신기술인 "차량탑재 모바일매핑 시스템(Mobile Mapping System : GPS-Van) 개발이 완료되었고, 이를 활용한 각종 지형공간정보의 수정 갱신 작업이 이루어지고 있기 때문에 이를 활용한 수치지도 수정갱신의 가능성에 대한 검토와 방법론에 대한 정립이 요구되고 있다. 따라서 본 연구에서는 국내에서 개발된 신기술인 GPS-Van을 이용한 수치지도 수정갱신을 위한 정확도 분석 및 오차의 영향 분석을 통하여 보다 높은 정밀도의 도로기반 수치지도 수정 갱신의 가능성 및 방안을 제시하고자 한다.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.634-640
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• 2015

This paper proposes a novel three-dimensional mapping algorithm in Omni-Directional Vision SLAM based on a fisheye image and laser scanner data. The performance of SLAM has been improved by various estimation methods, sensors with multiple functions, or sensor fusion. Conventional 3D SLAM approaches which mainly employed RGB-D cameras to obtain depth information are not suitable for mobile robot applications because RGB-D camera system with multiple cameras have a greater size and slow processing time for the calculation of the depth information for omni-directional images. In this paper, we used a fisheye camera installed facing downwards and a two-dimensional laser scanner separate from the camera at a constant distance. We calculated fusion points from the plane coordinates of obstacles obtained by the information of the two-dimensional laser scanner and the outline of obstacles obtained by the omni-directional image sensor that can acquire surround view at the same time. The effectiveness of the proposed method is confirmed through comparison between maps obtained using the proposed algorithm and real maps.