• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.93-98
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• 2013

Multi-temporal high resolution satellite images are essential data for efficient city analysis and monitoring. Yet even when acquired from the same location, identical sensors as well as different sensors, these multi-temporal images have a geometric inconsistency. Matching points between images, therefore, must be extracted to match the images. With images of an urban area, however, it is difficult to extract matching points accurately because buildings, trees, bridges, and other artificial objects cause shadows over a wide area, which have different intensities and directions in multi-temporal images. In this study, we analyze a shadow effect on image matching of high resolution satellite images in urban area using Scale-Invariant Feature Transform(SIFT), the representative matching points extraction method, and automatic shadow extraction method. The shadow segments are extracted using spatial and spectral attributes derived from the image segmentation. Also, we consider information of shadow adjacency with the building edge buffer. SIFT matching points extracted from shadow segments are eliminated from matching point pairs and then image matching is performed. Finally, we evaluate the quality of matching points and image matching results, visually and quantitatively, for the analysis of shadow effect on image matching of high resolution satellite image.

• Journal of Biomedical Engineering Research
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• v.21 no.4
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• pp.333-338
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• 2000

In this paper, an automated segmentation algorithm is proposed for MR brain images using T1-weighted, T2-weighted, and PD images complementarily. The proposed segmentation algorithm is composed of 3 step. In the first step, cerebrum images are extracted by putting a cerebrum mask upon the three input images. In the second step, outstanding clusters that represent inner tissues of the cerebrum are chosen among 3-dimensional(3D) clusters. 3D clusters are determined by intersecting densely distributed parts of 2D histogram in the 3D space formed with three optimal scale images. Optimal scale image is made up of applying scale space filtering to each 2D histogram and searching graph structure. Optimal scale image best describes the shape of densely distributed parts of pixels in 2D histogram and searching graph structure. Optimal scale image best describes the shape of densely distributed parts of pixels in 2D histogram. In the final step, cerebrum images are segmented using FCM algorithm with its initial centroid value as the outstanding clusters centroid value. The proposed cluster's centroid accurately. And also can get better segmentation results from the proposed segmentation algorithm with multi spectral analysis than the method of single spectral analysis.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.82-89
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• 2012

This paper presents the intelligent tracking algorithm for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. Fuzzy c-mean clustering and predicted impact point are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by fuzzy c-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. The filtering process in a series of the algorithm which estimates the target value recognize the nonlinear maneuvering target as linear one because the filter recognize only remained noise by extracting acceleration from the positional error. After filtering process, we get the estimates target by compensating extracted acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. To maximize the effectiveness of the proposed system, we construct the multiple model structure. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.6
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• pp.621-629
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• 2008

This paper presents a low temperature co-fire ceramics(LTCC) Upconverter for a Ka-band OBS satellite transponder in order for size reduction which is one of the most important requirement for satellite components. A S-band low-pass filter(LPF), a K-band band-pass filter(BPF), and an upconverting MMIC mixer are embedded in the multi-layer structure of the upconverter. All spurious can be selectively rejected by employing a modified Elliptic low pass filter with a multi-pole structure for the S-band LPF. Also an improved performance of out-of-band rejection can be obtained. At the K-band BPF design a layer coupled configuration is employed. The upconverting mixer is an MMIC diode mixer with a double-balanced configuration. Conversion loss and isolation of the upconverter are 9 dB and 51 dBc, respectively. The size of the LTCC upconverter is only $8{\times}7{\times}0.6mm^3$ which is one-third for the thin-film based upconverter.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.919-927
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• 2019

In this paper, we propose an accurate camera calibration method for acquiring multiview stereoscopic images. Generally, camera calibration is performed by using checkerboard structured patterns. The checkerboard pattern simplifies feature point extraction process and utilizes previously recognized lattice structure, which results in the accurate estimation of relations between the point on 2-dimensional image and the point on 3-dimensional space. Since estimation accuracy of camera parameters is dependent on feature matching, accurate detection of checkerboard corner is crucial. Therefore, in this paper, we propose the method that performs accurate camera calibration method through accurate detection of checkerboard corners. Proposed method detects checkerboard corner candidates by utilizing 1-dimensional gaussian filters with succeeding corner refinement process to remove outliers from corner candidates and accurately detect checkerboard corners in sub-pixel unit. In order to verify the proposed method, we check reprojection errors and camera location estimation results to confirm camera intrinsic parameters and extrinsic parameters estimation accuracy.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1827-1836
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• 2022

Disasters that occur unexpectedly are difficult to predict. In addition, the scale and damage are increasing compared to the past. Sometimes one disaster can develop into another disaster. Among the four stages of disaster management, search and rescue are carried out in the response stage when an emergency occurs. Therefore, personnel such as firefighters who are put into the scene are put in at a lot of risk. In this respect, in the initial response process at the disaster site, robots are a technology with high potential to reduce damage to human life and property. In addition, Light Detection And Ranging (LiDAR) can acquire a relatively wide range of 3D information using a laser. Due to its high accuracy and precision, it is a very useful sensor when considering the characteristics of a disaster site. Therefore, in this study, development and experiments were conducted so that the robot could perform real-time monitoring at the disaster site. Multi-sensor module was developed by combining LiDAR, Inertial Measurement Unit (IMU) sensor, and computing board. Then, this module was mounted on the robot, and a customized Simultaneous Localization and Mapping (SLAM) algorithm was developed. A method for stably mounting a multi-sensor module to a robot to maintain optimal accuracy at disaster sites was studied. And to check the performance of the module, SLAM was tested inside the disaster building, and various SLAM algorithms and distance comparisons were performed. As a result, PackSLAM developed in this study showed lower error compared to other algorithms, showing the possibility of application in disaster sites. In the future, in order to further enhance usability at disaster sites, various experiments will be conducted by establishing a rough terrain environment with many obstacles.

• 한국지구물리탐사학회:학술대회논문집
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• 2002.09a
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• pp.24-45
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• 2002

For the last several decades, high-resolution shallow marine seismic technique has been used for various resources, engineering and geological surveys. Even though the multichannel method is powerful to image subsurface structures, single channel analog survey has been more frequently employed in shallow water exploration, because it is more expedient and economical. To improve the quality of the high-resolution seismic data economically, we acquired digital seismic data using a small air gun, 6 channel streamer and PC-based system, performed data processing and produced high-resolution seismic sections. For many years, such test acquisitions were performed with other studies which have different purposes in the area of off Pohang, Yellow Sea and Gyeonggi-bay. Basic data processing was applied to the acquired data and the processing sequence included gain recovery, deconvolution, filtering, normal moveout, static corrections, CMP gathering and stacking. Examples of digitally processed sections were shown and compared with analog sections. Digital seismic sections have a much higher resolution after data processing. The results of acquisition and processing show that the high-resolution shallow marine seismic surveys using a small air gun, 6 channel streamer and PC-based system may be an effective way to image shallow subsurface structures precisely.

• Journal of Advanced Navigation Technology
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• v.13 no.3
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• pp.311-318
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• 2009

This paper shows the research about the development of software receiving platform processing GPS/Galileo L1/E1/E5a signal. Various researches for new GNSS signal character are possible using software receiving platform by facile program code modification. In addition, the program that processes GPS and Galileo signal integration is expected to help developing integration of receiver algorithm that deal with new various GNSS signal. In this paper, it is introduced the structure of GPS/Galileo receiving platform using sampled IF data as a program input. The function of the software platform embodied using MATLAB tool is tested by live data from Galileo test satellites. The software platform is modulated according to their roll and function. Each module is able to use selective function on GNSS signal.

• Journal of Korea Technology Innovation Society
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• v.19 no.2
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• pp.254-279
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• 2016

Recently, with the conversion towards knowledge-based economy era, the importance of the evaluation for patent valuation has been growing rapidly because technology transactions are increasing with the purpose of practically utilizing R&D outcomes such as technology commercialization and technology transfer. Nevertheless, there is a lack of research on determinants of patent valuation by analyzing technology transactions due to the difficulty of collecting data in practice. Hence, to suggest quantitative determinants for the patent valuation which could be applied to scoring methods, 15 patent valuation models domestically and overseas are analysed in order to assure the objectiveness for subjective results from qualitative methods such as expert surveys, comparison assessment, etc. Through this analysis, the important 6 common determinants are drawn and patent information is matched which can be used as proxy variables of individual determinant factors by advanced researches. In addition, to validate whether the model proposed has a statistically meaningful effect, total 517 technology transactions are collected from both public and private technology transaction offices and analysed by multiple regression analysis, which led to significant patent determinant factors in deciding its value. As a result, it is herein presented that patent connectivity(number of literature cited) and commercialization stage in market influence significantly on patent valuation. The meaning of this study is in that it suggests the significant quantitative determinants of patent valuation based on the technology transactions data in practice, and if research results by industry are systematically verified through seamless collection of transaction data and their monitoring, we would propose the customized patent valuation model by industry which is applicable for both strategic planning of patent registration and achievement assessment of research projects (with representative patents).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.1
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• pp.1-10
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• 2013

In this paper, a broadband planar monopole antenna for multi-band services is proposed. The physical size of the proposed antenna is miniaturized by folding a rectangular loop. And a resonance point in the 3.9 GHz band is reduced by a coupling phenomenon with the central part of the T-shaped patch and the folded rectangular loop. In addition, the T-shaped patch is inserted to the rectangular shaped monopole antenna due to deriving the broadband frequency characteristics. The frequency characteristic is optimized by adjusting the gap and length of the folded rectangular loops and a transverse diameter of the T-shaped patch. The antenna dimensions including the ground plane are $40{\times}60{\times}1.6mm^3$. It is fabricated on the FR-4 substrate(${\epsilon}_r$=4.4) using a microstrip line of $50{\Omega}$ for impedance matching. In the measured result, the bandwidth corresponding to the VSWR of 2:1 is 162 MHz(815~977 MHz) and 2,530 MHz(1.43~3.96 GHz). For analyzing the human effect by the proposed antenna, 1 g and 10 g averaged SARs are simulated and measured. As the simulated results, 1 g-averaged SAR is 1.044 W/kg, and 10 g-averaged SAR is 0.718 W/kg. This result are satisfied by the SAR guidelines which are 1.6 W/kg(1 g-averaged) and 2.0 W/kg(10 g-averaged).