• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.119-124
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• 2009

In this paper, we propose a novel approach to estimating the real-time moving trajectory of an object is proposed in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the input-output relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• Journal of the Korean Society of Visualization
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• v.3 no.1
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• pp.3-19
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• 2005

Novel optical techniques are presented for three-dimensional tracking of nanoparticles; Optical Serial Sectioning Microscopy (OSSM) and Ratiometric Total Internal Reflection Fluorescent Microscopy (R-TIRFM). OSSM measures optically diffracted particle images, the so-called Point Spread Function (PSF), and dotermines the defocusing or line-of-sight location of the imaged particle measured from the focal plane. The line-of-sight Brownian motion detection using the OSSM technique is proposed in lieu of the more cumbersome two-dimensional Brownian motion tracking on the imaging plane as a potentially more effective tool to nonintrusively map the temperature fields for nanoparticle suspension fluids. On the other hand, R-TIRFM is presented to experimentally examine the classic theory on the near-wall hindered Brownian diffusive motion. An evanescent wave field from the total internal reflection of a 488-nm bandwidth of an argon-ion laser is used to provide a thin illumination field of an order of a few hundred nanometers from the wall. The experimental results show good agreement with the lateral hindrance theory, but show discrepancies from the normal hindrance theory. It is conjectured that the discrepancies can be attributed to the additional hindering effects, including electrostatic and electro-osmotic interactions between the negatively charged tracer particles and the glass surface.

• Economic and Environmental Geology
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• v.29 no.5
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• pp.615-622
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• 1996

Slope stability analysis was conducted using remote sensing and Geoscientific Information System (GIS) as a part of natural hazard assessment around Chungju area. Landsat TM band 5 and 7 which contain more information about geological structure and geography are chosen and processed to analyse regional geological structure. Through image processing technique such as PCA, HFF, edge detection and enhancement, regional lineament can be mapped and identified. The lineament density map is constructed based on summed length of lineaments per unit area and the study area can be divided into 7 structural domains. Various factors of slope stability analysis such as geology, slope aspect, degree of slope, landcover, water shed as well as characterized structural domain are constructed as a database of GIS. Rating and weighting of each factor for slope stability analysis is decided by considering environmental geological characteristics of study area. Spatial analysis of regional slope stability is examined through overlaying technique of the GIS. The result of areal distribution of slope stability shows that the most unstable area is all over Jaeogae-ni, Hyangsan-ni and Mt. Daedun.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.6
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• pp.531-538
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• 2016

In this paper, we design and fabricate a short range FMCW radar which detects and tracks a moving target in a two-dimensional domain using dual transceiver modules. For the short range radar, we propose a scheme for alternate extraction of the two-dimensional positions using one-dimensional range information from time division transceiver modules, and successfully apply the scheme to the two-dimensional short range radar. Measured results of the targets at 10 m and 30 m are presented as performance demonstration of each transceiver module. Also the performance of the two-dimensional radar is demonstrated using a two-dimensional target map, which uses the range bin corresponding to the frequency resolution, and the effectiveness of the proposed scheme is validated.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.99-106
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• 2007

In this paper, we present an AAW(Adaptive Attention Window) based cell image segmentation method. For semantic AAW detection we create an initial Attention Window by using a luminance map. Then the initial AW is reduced to the optimal size of the real ROI(Region of Interest) by using a quad tree segmentation. The purpose of AAW is to remove the background and to reduce the amount of processing time for segmenting ROIs. Experimental results show that the proposed method segments one or more ROIs efficiently and gives the similar segmentation result as compared with the human perception.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.547-557
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• 2016

Due to threats caused by social disasters, operating surveillance devices are essential for social safety. CCTV, infrared cameras and other surveillance equipment are used to observe threats. This research proposes a method for searching for the optimum location of surveillance sensors. A GA (Genetic Algorithm) was used, since this algorithm is one of the most reasonable and efficient methods for solving complex non-linear problems. The sensor specifications, a DEM (Digital Elevation Model) and VITD (Vector Product Interim Terrain Data) maps were used for input data. We designed a chromosome using the sensor pixel location, and used elitism selection and uniform crossover for searching final solution. A fitness function was derived by the number of detected pixels on the borderline and the sum of the detection probability in the surveillance zone. The results of a 5-sensor and a 10-sensor were compared and analyzed.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.359-367
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• 2011

A suitable pan-sharpening method has to be chosen with respect to the used spectral characteristic of the multispectral bands and the intended application. The research on pan-sharpening algorithm in improving the accuracy of image classification has been reported. For a classification, preserving the spectral information is important. Other applications such as road detection depend on a sharp and detailed display of the scene. Various criteria applied to scenes with different characteristics should be used to compare the pan-sharpening methods. The pan-sharpening methods in our research comprise rather common techniques like Brovey, IHS(Intensity Hue Saturation) transform, and PCA(Principal Component Analysis), and more complex approaches, including wavelet transformation. The extraction of matching pairs was performed through SIFT descriptor and Canny edge detector. The experiments showed that pan-sharpening techniques for spatial enhancement were effective for extracting point and linear features. As a result of the validation it clearly emphasized that a suitable pan-sharpening method has to be chosen with respect to the used spectral characteristic of the multispectral bands and the intended application. In future it is necessary to design hybrid pan-sharpening for the updating of features and land-use class of a map.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.21-28
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• 2017

The main goal of this paper is to assess application of UAV (Unmanned Aerial Vehicle) remote sensing and GIS based images in detection and measuring of rice field drought area in South Korea. Drought is recurring feature of the climatic events, which often hit South Korea, bringing significant water shortages, local economic losses and adverse social consequences. This paper describes the assesment of the near-realtime drought damage monitoring and reporting system for the agricultural drought region. The system is being developed using drought-related vegetation characteristics, which are derived from UAV remote sensing data. The study area is $3.07km^2$ of Wonbuk-myeon, Taean-gun, Chungnam in South Korea. UAV images were acquired three times from July 4 to October 29, 2015. Three images of the same test site have been analysed by object-based image classification technique. Drought damaged paddy rices reached $754,362m^2$, which is 47.1 %. The NongHyeop Agricultural Damage Insurance accepted agricultural land of 4.6 % ($34,932m^2$). For paddy rices by UAV investigation, the drought monitoring and crop productivity was effective in improving drought assessment method.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.31-37
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• 2020

Last year's Goseong-Sokcho forest fires have highlighted the limitations of extinguishing work for night-time forest fire and the importance of quick identification for information on the spread of forest fire. However, it is not easy to find services that take into account the characteristics of forest fires, as most existing disaster-related mobile applications and research assume various disaster situations rather than just forest fire situations. Therefore, a system that can provide information quickly is needed, taking into account the characteristics of forest fires and the limitations of extinguishing work. In this paper, we propose evacuation route guidance services that bypass areas where fire has already spread, supplement existing methods of extinguishing work, and provide general information on forest fire situations in real time, by putting drones into forest fire situations. It has been implemented to automate image analysis using the Rekognition service of Amazon Web Service (AWS), and the results of fire detection and the T Map API guide the evacuation path. It is expected that the results of this paper will allow efficient and rapid rescue and extinguishing work to be carried out, and further reduce the damage of human life caused by forest fires.

• Journal of Aerospace System Engineering
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• v.8 no.2
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• pp.40-48
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• 2014

In this paper, a prototype of GPS jammer localization system for precise landing is developed. The jammer localization system consists of the four jamming signal receivers for collecting RF signal, one central tracking station for estimating jammer position, and one monitoring station for displaying estimated position on the map. In order to estimate jammer location TDOA and AOA algorithm are introduced, and the function and design parameters of the developed prototype are proposed. CW, DSSS, Swept CW jamming signals were generated and used. From the results, it can be confirmed that developed system meets the performance goal.