• Journal of KIISE:Computer Systems and Theory
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• v.35 no.5
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• pp.213-222
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• 2008

This paper is related to color image segmentation and textile texture mapping for the 2D virtual wearing system. The proposed system is characterized as virtually wearing a new textile pattern selected by user to the clothing shape section, based on its intensity difference map, segmented from a 2D clothes model image using color image segmentation technique. Regardless of color or intensity of model clothes, the proposed system is possible to virtually change the textile pattern or color with holding the illumination and shading properties of the selected clothing shape section, and also to quickly and easily simulate, compare, and select multiple textile pattern combinations for individual styles or entire outfits. The proposed system can provide higher practicality and easy-to-use interface, as it makes real-time processing possible in various digital environment, and creates comparatively natural and realistic virtual wearing styles, and also makes semi-automatic processing possible to reduce the manual works to a minimum. According to the proposed system, it can motivate the creative activity of the designers with simulation results on the effect of textile pattern design on the appearance of clothes without manufacturing physical clothes and, as it can help the purchasers for decision-making with them, promote B2B or B2C e-commerce.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.1 s.19
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• pp.19-26
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• 2002

To provide 3D GSIS data on the internet, 3D data structures need to be researched and applied for spatial analysis for subsurface modeling. As for GSIS software R&D trend the following things have pointed out : 3-dimensional geo-processing technologies, internet-based application system development, distributed processing technologies for large volume of spatial information, real-time geo-data processing methodologies, Among them research scope within Internet-based application system or Web-based GSIS generally contains core parts of software development such as Internet application, large volume of spatial database handling, real-time spatial data processing, spatial data transfer and transformation, and volumetric display of processing results. This study shows the method of providing 3D GSIS on the internet using VRML model, which are made of DEM data, draped aerial photo, and VRML script programming. And it is also studied that offering 3D GSIS engine on the internet and precise texture mapping using satellite image and aerial photos.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.58-63
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• 2017

Emergencies and disasters can happen any time without any warning, and things can change and escalate very quickly, and often it is swift and decisive actions that make all the difference. It is a responsibility of the building facility management to ensure that a proven evacuation plan in place to cover various worst scenario to handled automatically inside the facility. To mapping out optimal safe escape routes is a straightforward undertaking, but does not necessarily guarantee residents the highest level of protection. The emergency evacuation navigation approach is a state-of-the-art that designed to evacuate human livings during an emergencies based on real-time decisions using live sensory data with pre-defined optimum path finding algorithm. The poor decision on causalities and guidance may apparently end the evacuation process and cannot then be remedied. This paper propose a cloud connected emergency evacuation system model to react dynamically to changes in the environment in emergency for safest emergency evacuation using IoT based emergency exit sign system. In the previous researches shows that the performance of optimal routing algorithms for evacuation purposes are more sensitive to the initial distribution of evacuees, the occupancy levels, and the type and level of emergency situations. The heuristic-based evacuees routing algorithms have a problem with the choice of certain parameters which causes evacuation process in real-time. Therefore, this paper proposes an evacuee routing algorithm that optimizes evacuation by making using high computational power of cloud servers. The proposed algorithm is evaluated via a cloud-based simulator with different "simulated casualties" are then re-routed using a Dijkstra's algorithm to obtain new safe emergency evacuation paths against guiding evacuees with a predetermined routing algorithm for them to emergency exits. The performance of proposed approach can be iterated as long as corrective action is still possible and give safe evacuation paths and dynamically configure the emergency exit signs to react for real-time instantaneous safe evacuation guidance.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1934-1935
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• 2011

In order for a service robot to perform several tasks, basically autonomous navigation technique such as localization, mapping, and path planning is required. The localization (estimation robot's pose) is fundamental ability for service robot to navigate autonomously. In this paper, we propose a new system for point pattern matching based visual global localization using spot lightings in ceiling. The proposed algorithm us suitable for system that demands high accuracy and fast update rate such a guide robot in the exhibition. A single camera looking upward direction (called ceiling vision system) is mounted on the head of the mobile robot and image features such as lightings are detected and tracked through the image sequence. For detecting more spot lightings, we choose wide FOV lens, and inevitably there is serious image distortion. But by applying correction calculation only for the position of spot lightings not whole image pixels, we can decrease the processing time. And then using point pattern matching and least square estimation, finally we can get the precise position and orientation of the mobile robot. Experimental results demonstrate the accuracy and update rate of the proposed algorithm in real environments.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.4
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• pp.329-338
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• 2022

This paper provides a case study of development testing and evaluation of design goal of Interferometric SAS (Synthetic Aperture Sonar) system that is developing supported by Civil-Military Technology Cooperation Center in offshore fields. For Deep water operating capabilities evaluation, We have surveyed candidate field, bathymetric mapping and target identification over 200 m depth, East Sea. In testing phase, We have provided environmental information of testing field include water column, seabed and weather condition in real time. And to compare excellency of developing InSAS, we have gather commercial imaging sonar system data with same target. This case study will support the Test Readiness Review of future underwater surveillance system developing via investigate marine testing field environment, testing facilities and planning.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.10-16
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• 2012

For high speed visual inspection in semiconductor industries, it is essential to acquire two-dimensional images on regions of interests with a large field of view (FOV) and a high resolution simultaneously. In this paper, an imaging system is newly proposed to achieve high quality image in terms of precision and FOV, which is composed of single lens, a beam splitter, two camera sensors, and stereo image grabbing board. For simultaneously acquired object images from two camera sensors, Zhang's camera calibration method is applied to calibrate each camera first of all. Secondly, to find a mathematical mapping function between two images acquired from different view cameras, the matching matrix from multiview camera geometry is calculated based on their image homography. Through the image homography, two images are finally registered to secure a large inspection FOV. Here the inspection system of using multiple images from multiple cameras need very fast processing unit for real-time image matching. For this purpose, parallel processing hardware and software are utilized, such as Compute Unified Device Architecture (CUDA). As a result, we can obtain a matched image from two separated images in real-time. Finally, the acquired homography is evaluated in term of accuracy through a series of experiments, and the obtained results shows the effectiveness of the proposed system and method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.72-77
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• 2014

There are two main technologies to implement cloud effect in flight simulator, cloud modeling using particle system and texture mapping. In former case, this approach may cause a low frame rate while unrealistic cloud effect is observed in latter case. To Solve this problem, in this paper, we propose how to apply fog effect into camera to display more realistic cloud effect with high frame rate. The proposed method is tested with massive terrain database environment through implemented software by using OpenSceneGraph. As a result, compared to texture mapping method, the degree of difference on frame rate is 1 or 2Hz while the cloud effect is significantly improved as realistic as particle system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.12 s.103
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• pp.1229-1238
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• 2005

OFDM(Orthogonal Frequency Division Multiplexing) communications system is very attractive for the high data rate wireless transmission. However, it may be distorted in the nonlinear HPA(High Power Amplifier) since OFDM signal has hish PAPR(Peak-to-Average Power Ratio). In this paper, a new method using control tone is studied for reducing the PAPR and we call it PCT(PAPR Control Tone) method. This proposed PCT method is to assign control tones for PAPR reduction at the predefined sub-carriers. After IFFT(Inverse Fast Fourier Transform) and PAPR calculation, the OFDM data signal of the lowest PAPR is selected to transmit. Unlike the conventional method, it can cut down the computational complexity because it does not require the transmission and demodulation process of side information about the phase rotation. Furthermore, if this method is made up in parallel configuration, it can solve the time delay problem so that it can be processed in real time processing. This proposed method is compared with the conventional selected mapping(SLM) technique. We find out the PAPR reduction performance and BER when the number of control tone is 6 and nonlinear HPA is considered.

• 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.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.740-743
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• 1998

This paper presents an optimization algorithm for a stable Dynamic Neural Network (DNN) using genetic algorithm. Optimized DNN is applied to a problem of controlling nonlinear dynamical systems. DNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. The real time implementation is very important, and thus the neuro controller also needs to be designed such that it converges with a relatively small number of training cycles. SDNN has considerably fewer weights than DNN. The object of proposed algorithm is to the number of self dynamic neuron node and the gradient of activation functions are simultaneously optimized by genetic algorithms. To guarantee convergence, an analytic method based on the Lyapunov function is used to find a stable learning for the SDNN. The ability and effectiveness of identifying and controlling, a nonlinear dynamic system using the proposed optimized SDNN considering stability' is demonstrated by case studies.