• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.417-422
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• 2003

The KOMPSAT-2 MSC(Multi-Spectral Camera), with high spatial resolution, is currently under development and will be launched in the end of 2004. A sensor model relates a 3-D ground position to the corresponding 2-D image position and describes the imaging geometry that is necessary to reconstruct the physical imaging process. The Rational Function Model (RFM) has been considered as a generic sensor model. form. The RFM is technically applicable to all types of sensors such as frame, pushbroom, whiskbroom and SAR etc. With the increasing availability of the new generation imaging sensors, accurate and fast rectification of digital imagery using a generic sensor model becomes of great interest to the user community. This paper describes the procedure to generation of the RPC (Rational Polynomial Coefficients) for KOMPSAT-2 MSC.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.1
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• pp.49-56
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• 1994

This paper describes the design principles and methods of electronic processor for thermal imager with the SPRITE detector, operating in the 8-12 micron band. The thermal imager consists of a optical scanner containing the detector and an electrical signal processor. The optical scanner utilizing rotating polygon and oscillating mirror, is 2-dimensional serial/parallel scan type using 5 elements of the detector. And the electronic processor has pre-processing of 5 chnanel's thermal signal from the detector, and performs digital scan conversion to reform the parallel data stream into serial analog data compatible with conventional RS-170 video. Through the designed electronic processor, we have acquired a satisfactory thermal image. And the MRTD (Minimum Resolvable Temperature Difference) is 0.5$^{\circ}$K at 7.5 cycles/mm.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.313-317
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• 2003

This paper suggested the initial edge map through the pre-processing of vague image before apply the GVF snake algorithm. The reason obtain for detail object outline and time efficiency GVF snake algorithm feasible extracted concave edge but mistake interested object edge for the around others. So it need to trim about the object around edges. The method is using Pixel morphological reconstruction, edge extraction mask and threshoding. The result, defend fallen local minimum edge energy and reduce iteration.

• Journal of the Korean Society of Safety
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• v.31 no.2
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• pp.33-40
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• 2016

Liquid fuel can be easily exploded and release more energy of detonation than conventional explosives because it has different explosion mechanism. In order to analyze dispersion characteristics of liquid fuel for the safety purpose, two tests are conducted. First, pre-test, which is a computer simulation, is carried out by a software called ANSYS AUTODYN to eliminate the effect of a canister that usually causes irregular dispersion of the fuel. Second, field test is performed to find out the amount and density effect of bursting charge. High speed cameras are installed in front of the canister to visualize the mechanism. Velocity, area and radius of the dispersed cloud are measured by image processing software, these are shown that the amount of bursting charge affects cloud velocity and area but density is not a significant factor of cloud formation.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.235-238
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• 2019

In real world object detection is an active research topic for understanding different objects from images. There are different models presented in past and had significant results. In this paper we are presenting vehicle logo detection using previous object detection models such as You only look once (YOLO) and Faster Region-based CNN (F-RCNN). Both the front and rear view of the vehicles were used for training and testing the proposed method. Along with deep learning an image pre-processing algorithm called perspective transformation is proposed for all the test images. Using perspective transformation, the top view images were transformed into front view images. This algorithm has higher detection rate as compared to raw images. Furthermore, YOLO model has better result as compare to F-RCNN model.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.425-427
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• 2004

Motivation of this study is based on these two aspects: geologic uses of ASTER and application scheme of Spectral Mixture Analysis. This study aims at geologic mapping for mineral exploration using ASTER and LANDSAT 7 ETM+ at Mongolian plateau region by SMA. After basic pre-processing such as the normalization, geometric corrections and calibration of reflectance, related to endmembers selection and spectral signature deviation, both methods using spectral library and using PPI(Pixel Purity Index) are performed and compared on a given task. Based on these schemes, SMA is performed using LANDSAT 7 ETM+ and ASTER image. As the results, fraction map showing geologic rock types are enough to meet purposes such as geologic mapping and mineral potential mapping in the case of both uses of these different types of remotely sensed images. It concluded that this approach based on SMA with LANDSAT and ASTER is regarded as one of effective schemes for geologic remote sensing.

• Proceedings of the KSRS Conference
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• v.2
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• pp.619-622
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• 2006

Atmospheric correction is one of critical procedures to extract quantitative information related to biophysical variables from hyperspectral data. In this study, we attempted to generate the water vapor contents image from hyperspectral data itself and developed the atmospheric correction algorithm for EO-1 Hyperion data using pre-calculated atmospheric look-up-table (LUT) for fast processing. To apply the new atmospheric correction algorithm, Hyperion data acquired June 3, 2001 over Seoul area is used. Reflectance spectrums of various targets on atmospheric corrected Hyperion reflectance images showed the general spectral pattern although there must be further development to reduce the spectral noise.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.321-324
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• 2003

This paper presents a novel system that analyzes and recognizes a gait based on shape context on silhouette images. The main functions of the system consist of three steps: First, the system extracts the silhouette images from galt image sequence by performing a simple pre-processing and acquires the AGM(Averaged Gait Map) by averaging them. Next. it computes the cross-correlation between the AGMs. Finally, it classifies the AGMs based on the cross-correlation using nearest neighborhood classification. The proposed system uses two cues to classify a gait: One corresponds to biometric shape cue such as body height width. and body-part proportions. The other corresponds to gait cue such as stride length and amount of arm swing. Perceptionally, the biometric cues are sailent on the double support (both legs spread and touching the ground) while the gait cues on the midstance. Through a variety of experiments, it is proved that the property of a gait is mainly influenced by gait cues than biometric cues.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.1
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• pp.43.3-44
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• 2017

We report the operational highlights of KMTNet in the point of observing rate, image pre-processing and data reduction, observing run for each science program, and scientific publications performed in 2016. Major system upgrade has been conducted in the CCD camera and the wide field telescope optics: the post amp and readout electronics of the 18k Mosaic CCD camera at Siding Spring Observatory site has been fine tuned and the protected silver coat of the primary mirror has been replaced with the bare aluminium coat due to the degradation of reflectivity of the primary mirror surface. A plan of KMTNet observation system improvement for 2017 will be introduced in this talk.

• Journal of Korea Multimedia Society
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• v.18 no.2
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• pp.158-167
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• 2015

This study presents a new method to improve the speed of high quality volume rendering. We improve the speed of ambient occlusion which is one of the global illumination techniques used in traditional volume visualization. Calculating ambient occlusion takes much time because it determines an illumination value of a sample by integrating opacities of nearby samples. This study proposes an improved method for this by using local statistics such as averages and standard deviations. We calculate local statistics for each volume block, a set of nearby samples, in pre-processing time. In the rendering process, we efficiently determine the illumination value by assuming the density distribution as a normal distribution. As the results, we can generate high quality images that combine ambient occlusion illumination with local illumination in real time.