• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.99-106
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• 2008

A synthetic aperture radar (SAR) system is of great interest in many fields of civil and military applications because of all-weather and luminance free imaging capability. SAR image quality parameters such as spatial resolution, peak to sidelobe ratio (PSLR), and integrated sidelobe ratio (ISLR) can be normally estimated by modeling of impulse response function (IRF) which is obtained from various system design parameters such as altitude, operational frequency, PRF, etc. In modeling of IRF, however, background clutter environment surrounding the IRF is generally neglected. In this paper, analysis method for SAR mage quality is proposed in the real background clutter environment. First of all, SAR raw data of a point scatterer is generated based on various system parameters. Secondly, the generated raw data can be focused to ideal IRF by range Doppler algorithm (RDA). Finally, background clutter obtained from image of currently operating SAR system is applied to IRF. In addition, image quality is precisely analyzed by zooming and interpolation method for effective extraction of IRF, and then the effect of proposed methodology is presented with several simulation results under the assumption of estimation error of Doppler rate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.225-227
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• 2022

Now In Seoul, about 75,000 CCTVs are installed in 25 district offices. Each ward office in Seoul has built a control center for CCTV control and is building information such as people, vehicle types, license plate recognition and color classification into big data through 24-hour artificial intelligence intelligent image analysis. Seoul Metropolitan Government has signed MOUs with the Ministry of Land, Infrastructure and Transport, the National Police Agency, the Fire Service, the Ministry of Justice, and the military base to enable rapid response to emergency/emergency situations. In other words, we are building a smart city that is safe and can prevent disasters by providing CCTV images of each ward office. In this paper, the CCTV image is designed to extract the characteristics of the vehicle and personnel when an incident occurs through artificial intelligence, and based on this, predict the escape route and enable continuous tracking. It is designed so that the AI automatically selects and displays the CCTV image of the route. It is designed to expand the smart city integration platform by providing image information and extracted information to the adjacent ward office when the escape route of a person or vehicle related to an incident is expected to an area other than the relevant jurisdiction. This paper will contribute as basic data to the development of smart city integrated platform research.

• Journal of the Korean Geographical Society
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• v.43 no.2
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• pp.188-201
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• 2008

With recent rapid globalization, accurate information for the foreign countries is increasingly important. Errors based on inaccurate information and unequal international relationships complicate the situations. In this article, authors analyzed the Japanese place names which appear on the Google Earth images and place name database of the NGA. Google Earth already becomes a tremendous soft power in internet society; therefore, accurate information on the satellite image is more necessary than ever. This article finds that many types of errors exist in the place names in Google Earth image service. Also many place names are listed with Japanese pronunciation in GNS database as variants. The Japanese place names have not been used in topographic maps published since 1910s and 1930s. Japanese place names were widely used in US military maps published in 1946. 1:250,000 maps published in 1954, however, doesn't seem to use Japanese pronunciation any more.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1543-1561
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• 2020

Taxonomy of human brain activity is a complicated rather challenging procedure. Due to its multifaceted aspects, including experiment design, stimuli selection and presentation of images other than feature extraction and selection techniques, foster its challenging nature. Although, researchers have focused various methods to create taxonomy of human brain activity, however use of multivariate pattern analysis (MVPA) for image recognition to catalog the human brain activities is scarce. Moreover, experiment design is a complex procedure and selection of image type, color and order is challenging too. Thus, this research bridge the gap by using MVPA to create taxonomy of human brain activity for different categories of images, both colored and gray scale. In this regard, experiment is conducted through EEG testing technique, with feature extraction, selection and classification approaches to collect data from prequalified criteria of 25 graduates of University Technology PETRONAS (UTP). These participants are shown both colored and gray scale images to record accuracy and reaction time. The results showed that colored images produces better end result in terms of accuracy and response time using wavelet transform, t-test and support vector machine. This research resulted that MVPA is a better approach for the analysis of EEG data as more useful information can be extracted from the brain using colored images. This research discusses a detail behavior of human brain based on the color and gray scale images for the specific and unique task. This research contributes to further improve the decoding of human brain with increased accuracy. Besides, such experiment settings can be implemented and contribute to other areas of medical, military, business, lie detection and many others.

• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.1-10
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• 2018

This paper presents an autonomous detection and aiming point computation of a battle tank by using RGB images. Maximally stable extremal regions algorithm was implemented to find features of the tank, which are matched with images extracted from streaming video to figure out the region of interest where the tank is present. The median filter was applied to remove noises in the region of interest and decrease camouflage effects of the tank. For the tank segmentation, k-mean clustering was used to autonomously distinguish the tank from its background. Also, both erosion and dilation algorithms of morphology techniques were applied to extract the tank shape without noises and generate the binary image with 1 for the tank and 0 for the background. After that, Sobel's edge detection was used to measure the outline of the tank by which the aiming point at the center of the tank was calculated. For performance measurement, accuracy, precision, recall, and F-measure were analyzed by confusion matrix, resulting in 91.6%, 90.4%, 85.8%, and 88.1%, respectively.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.77-87
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• 2012

Discussion on North Korea as UN-REDD (Reduced Emissions from Deforestation and Degradation in developing countries) project target continues with a view to preventing deforestation and to securing CER(certified emission reduction) for South Korea. However, due to North Korea's political shutdown, it is hard to acquire information required for the REDD project registration. This research intends to acquire objective data using satellite images in the Mt. Geumgang. More than 20% of entire forested area were disappeared during the past two decades mainly due to conversion into agricultural farming land. Further, it is expected that persistent deforestation will go on. The reduction potential of the carbon emission is estimated as approximately 617,000 tCO2/year~663.000 tCO2/year. Thus, Mt. Geumgang is considered as realistic REDD target, which is attractive to South Korea, given that the obligation to reduce greenhouse gas emission is likely to be imposed upon the country. Further, political and social benefits due to reduced military conflict make Mt. Geumgang as UN-REDD project target invaluable.

• Korean Journal of Optics and Photonics
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• v.17 no.2
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• pp.113-119
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• 2006

We need a good image of the retina of the human eye in order to inspect or cure it. In this work, an optical system design for a retinal camera is studied and the finite schematic eye model made by Sang Gee Kim and Sung Chan Park is used. The optical system is composed of four lens groups. The rays of the entire object field are collected on the center by the 1st group and the objective is imaged by all the other groups. The image is detected by the CCD array and displayed by a monitor The 1st lens group is employed singlet and other groups are employed triplets. Ray aberrations, spot diagrams, diffraction line spread functions and MTFs are calculated for optical performance assessment. This design may be very useful for the development of a retinal camera with high performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1645-1652
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• 2018

A drone which was developed first for military purpose has been expanded to various civil areas, with its technological development. Of the drones developed for such diverse purposes, a drone for photography has a camera installed and is actively applied to a variety of image contents making, beyond filming and broadcasting. A drone for photography makes it possible to shoot present and dynamic images which were hard to be photographed with conventional photography technology. This study made a view finder which helps a drone operator to control a drone and directly view an object to shoot with the drone camera. The view finder for drones is a type of glasses. It was developed in the way of printing out the data modelled with 3D MAX in a 3D printer and installing a ultra-small LCD monitor. The view finder for drones makes it possible to fly a drone safely and achieve accurate framing of an object to shoot.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.89-94
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• 2019

K1A1 tank commander's primary thermal sight is a device that enables tank commanders to detect, identify, aim and track the target by observing targets in all directions during day, night and in situations of smokescreen and fog through $360^{\circ}$ rotation independent from the gunner's primary thermal sight and stabilizing the line of sight even under the vibrations occurring when the tank is standstill and moving. The main function of this device is to detect and process visible and thermal images and deliver the final images to the tank commander. One of the core parts to that end is the observation window (daytime/thermal image window). This core part is mounted at the entrance of the optical path for observing the target and plays the role of making visible light during the daytime and infrared light during the night pass through the target and transmitting the resultant images to the internal optical system of the tank commander's primary thermal sight. Such core parts have been selected as depot maintenance items so that they are replaced by new parts instead of being recycled when they are subjected to maintenance in most cases. That is, the military budget is wasted because such parts are replaced by new parts despite that they can be recycled for maintenance. Therefore, this study proposed a mounting tool for polishing and coating observation windows (daytime and thermal image window) using planar polishing equipment and DLC (Diamond-Like Carbon) coating equipment. In addition, this study presented an amendment (proposal) of the Depot Maintenance Work Request (DMWR) already published to verify the performance of recycled products including the establishment of inspection standards for recycling processes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.190-197
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• 2020

Recently there was an incident that military radars, coastal CCTVs and other surveillance equipment captured a small rubber boat smuggling a group of illegal immigrants into South Korea, but guards on duty failed to notice it until after they reached the shore and fled. After that, the detection of such vessels before it reach to the Korean shore has emerged as an important issue to be solved. In the fields of marine navigation, Automatic Identification System (AIS) is widely equipped in vessels, and the vessels incessantly transmits its position information. In this paper, we propose a method of automatically identifying abnormally behaving vessels with AIS using convolutional autoencoder (CAE). Vessel anomaly detection can be referred to as the process of detecting its trajectory that significantly deviated from the majority of the trajectories. In this method, the normal vessel trajectory is gridded as an image, and CAE are trained with images from historical normal vessel trajectories to reconstruct the input image. Features of normal trajectories are captured into weights in CAE. As a result, images of the trajectories of abnormal behaving vessels are poorly reconstructed and end up with large reconstruction errors. We show how correctly the model detects simulated abnormal trajectories shifted a few pixel from normal trajectories. Since the proposed model identifies abnormally behaving ships using actual AIS data, it is expected to contribute to the strengthening of security level when it is applied to various maritime surveillance systems.