• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.74-84
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• 2017

Since a soldier manages a hand-held landmine detector by hands, it is necessary to develop a system that can detect the target quickly and accurately. However, the hand-held landmine detector used in Korea has a problem that it can only detect the metal mines. Therefore, it is important to solve the problem and to develop a hand-held landmine detection system suitable for the Korean environment. In this paper, we propose a hand-held landmine detection system suitable for the Korean environment using ground penetrating radar. The proposed system uses depth compensation, matched filtering, and frequency shifting filtering for preprocessing. Then, in the detection step, the system detects the target using the edge ratio. In order to evaluate the proposed system, we buried landmines in sandy loam which is most of the soil in Korea and obtained a set of ground penetrating radar data by using a hand-held landmine detector. By using the obtained data, we carried out some experiments on the size and position of the patch and the shifting frequency to find the optimal parameter values and measured the detection performance using the optimized values. Experimental results show that the proposed preprocessing algorithms are suitable for detecting all landmines at low false alarm rate and the performance of the proposed system is superior to that of previous works.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.267-273
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• 2011

In this paper, we proposed the method to detect brain tumor region in MR images. Our method is composed of 3 parts, detection of tumor slice, detection of tumor region and tumor boundary detection. In the tumor slice detection step, a slice which contains tumor regions is distinguished using symmetric analysis in 3D brain volume. The tumor region detection step is the process to segment the tumor region in the slice distinguished as a tumor slice. And tumor region is finally detected, using spatial feature and symmetric analysis based on the cluster information. The process for detecting tumor slice and tumor region have advantages which are robust for noise and requires less computational time, using the knowledge of the brain tumor and cluster-based on symmetric analysis. And we use the level set method with fast marching algorithm to detect the tumor boundary. It is performed to find the tumor boundary for all other slices using the initial seeds derived from the previous or later slice until the tumor region is vanished. It requires less computational time because every procedure is not performed for all slices.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.345-352
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• 2020

To preserve and restore tidal flats and prevent safety accidents, it is necessary to construct tidal flat topographic information including the exact location and shape of tidal creeks. In the tidal flats where the field surveying is difficult to apply, airborne LiDAR surveying can provide accurate terrain data for a wide area. On the other hand, we can economically obtain relatively high-resolution data from UAV (Unmanned Aerial Vehicle) surveying. In this study, we proposed the methodology to generate high-resolution topographic information of tidal flats effectively by integrating airborne LiDAR and UAV point clouds. For the purpose, automatic ICP (Iterative Closest Points) registration between two different datasets was conducted and tidal creeks were extracted by applying CSF (Cloth Simulation Filtering) algorithm. Then, we integrated high-density UAV data for tidal creeks and airborne LiDAR data for flat grounds. DEM (Digital Elevation Model) and tidal flat area and depth were generated from the integrated data to construct high-resolution topographic information for large-scale tidal flat map creation. As a result, UAV data was registered without GCP (Ground Control Point), and integrated data including detailed topographic information of tidal creeks with a relatively small data size was generated.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.33-42
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• 2016

In Korea, the address-point matching technique has been used to provide geocoding services. In fact, this technique brings the high positional accuracy. However, the quality of geocoding result can be limited, since it is significantly affected by data quality. Also, it cannot be used for the 3D address geocoding and the reverse geocoding. In order to alleviate issues, the paper has implemeted proposed geocoding methods, based on street-based addresses matching technique developed by US census bureau, for street-based addresses in Korea. Those proposed geocoding methods are illustrated in two ways; (1) street address-matching method, which of being used for not only 2D addresses representing a single building but also 3D addresses representing indoor space or underground building, and (2) reverse geocoding method, whichas converting a location point to a readable address. The result of street-based address geocoding shows 82.63% match rates, while the result of reverse geocoding shows 98.5% match rates within approximately 1.7(m) the average position error. According to the results, we could conclude that the proposed geocoding techniques enable to provide the LBS(Location Based Service). To develop the geocoding methods, the study has perfoermed by ignoring the parsing algorithms for address standardization as well as the several areas with unusual addresses, such as sub-urban areas or subordinate areas to the roads, etc. In the future, we are planning the improved geocoding methods for considering these cases.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.709-716
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• 2004

This paper describes an intelligent real-time monitoring system of a semiconductor processing equipment, which determines normal or not for a wafer in processing, using multiple time-series pattern recognition. The proposed system consists of three phases, initialization, learning and real-time prediction. The initialization phase sets the weights and tile effective steps for all parameters of a monitoring equipment. The learning phase clusters time series patterns, which are producted and fathered for processing wafers by the equipment, using LBG algorithm. Each pattern has an ACI which is measured by a tester at the end of a process The real-time prediction phase corresponds a time series entered by real-time with the clustered patterns using Dynamic Time Warping, and finds the best matched pattern. Then it calculates a predicted ACI from a combination of the ACI, the difference and the weights. Finally it determines Spec in or out for the wafer. The proposed system is tested on the data acquired from etching device. The results show that the error between the estimated ACI and the actual measurement ACI is remarkably reduced according to the number of learning increases.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.265-278
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• 2019

Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) data help to enable rapid emergency responses through detection of the artificial and natural disasters occurring at night. The DNB data without correction of lunar irradiance effect distributed by Korea Ocean Science Center (KOSC) has advantage for rapid change detection because of direct receiving. In this study, radiance differences according to the phase of the moon was analyzed for urban and mountain areas in Korean Peninsula using the DNB data directly receiving to KOSC. Lunar irradiance correction algorithm was proposed for the change detection. Relative correction was performed by regression analysis between the selected pixels considering the land cover classification in the reference DNB image during the new moon and the input DNB image. As a result of daily difference image analysis, the brightness value change in urban area and mountain area was ${\pm}30$ radiance and below ${\pm}1$ radiance respectively. The object based change detection was performed after the extraction of the main object of interest based on the average image of time series data in order to reduce the matching and geometric error between DNB images. The changes in brightness occurring in mountainous areas were effectively detected after the calibration of lunar irradiance effect, and it showed that the developed technology could be used for real time change detection.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.2
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• pp.155-161
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• 2019

Currently, numerous companies and institutes provide services using the Internet, and establish and operate Information Systems to manage them efficiently and reliably. The Information System implies the possibility of losing the ability to provide normal services due to a disaster or disability. It is preparing for this by utilizing a disaster recovery system. However, existing disaster recovery systems cannot perform normal recovery if files for system recovery are corrupted. In this paper, we proposed a system that can verify the integrity of the system recovery file and proceed with recovery by utilizing hyper-ledger fabric blockchain. The PBFT consensus algorithm is used to generate the blocks and is performed by the leader node of the blockchain network. In the event of failure, verify the integrity of the recovery file by comparing the hash value of the recovery file with the hash value in the blockchain and proceed with recovery. For the evaluation of proposed techniques, a comparative analysis was conducted based on four items: existing system recovery techniques and data consistency, able to data retention, recovery file integrity, and using the proposed technique, the amount of traffic generated was analyzed to determine whether it was actually applicable.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.101-107
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• 2020

Road surface measurement is an essential process for quantifying the degree and displacement of roughness in road surface management. For safer road surface management and quick maintenance, it is important to accurately measure the road surface while mounted on a vehicle. In this paper, we propose a sophisticated road surface measurement system that can be measured on a moving vehicle. The proposed road surface measurement system supports more accurate measurement of the road surface by using a high-performance line laser sensor. It is also possible to measure the transverse and longitudinal profile by matching the position information acquired from the RTK, and the velocity adaptive update algorithm allows a manager to monitor in a real-time manner. In order to evaluate the proposed system, the Gocator laser sensor, MRP module, and NVIDIA Xavier processor were mounted on a test mobile and tested on the road surface. Our evaluation results demonstrate that our system measures accurate profile base on the MSE. Our proposed system can be used not only for evaluating the condition of roads but also for evaluating the impact of adjacent excavation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.2
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• pp.201-211
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• 2012

This paper addresses a Full Disk Encryption hardware processor for SATA HDD in a single FPGA design, and shows its experimental result using an FPGA board. The proposed processor mainly consists of two blocks: the first block processes XTS-AES block cipher which is the IEEE P1619 standard of storage media encryption and the second block executes the interface between SATA Host (PC) and Device (HDD). To minimize the performance degradation, we designed the XTS-AES block with the 4-stage pipelined structure which can process a 128-bit block per 4 clock cycles and has 4.8Gbps (max) performance. Also, we implemented the proposed design with Xilinx ML507 FPGA board and our experiment showed 140MB/sec read/write speed in Windows XP 32-bit and a SATA II HDD. This performance is almost equivalent with the speed of the direct SATA connection without FDE devices, hence our proposed processor is very suitable for SATA HDD Full Disk Encryption environments.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.53-65
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• 2021

C-ITS(Cooperative Intelligent Transport System) that pursues traffic safety and convenience uses various sensors to generate traffic information. Therefore, it is necessary to improve the sensor-related technology to increase the efficiency and reliability of the traffic information. Recently, the role of CCTV in collecting video information has become more important due to advances in AI(Artificial Intelligence) technology. In this study, we propose to identify and track dynamic objects(vehicles, people, etc.) in CCTV images, and to analyze and provide information about them in various environments. To this end, we conducted identification and tracking of dynamic objects using the Yolov4 and Deepsort algorithms, establishment of real-time multi-user support servers based on Kafka, defining transformation matrices between images and spatial coordinate systems, and map-based dynamic object visualization. In addition, a positional consistency evaluation was performed to confirm its usefulness. Through the proposed scheme, we confirmed that CCTVs can serve as important sensors to provide relevant information by analyzing road conditions in real time in terms of road infrastructure beyond a simple monitoring role.