• 천문학논총
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• 제10권1호
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• pp.135-146
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• 1995

We have developed a graphic software for image processing of astronomical data obtained by observational equipment in Astronomical Observatory of Kyung Hee University. The essential hardware for running our computer program is simply composed of a PC with the graphic card to handle 256 colors and the color graphic monitor, including CCD camera system. Our software has been programmed in WINDOWS to provide good environments for users, by using various techniques of image processing on astronomical image data recorded in FITS format by KHCCD program(Jin and Kim, 1994) with a compressional mode. We are convinced that our results will be a fundamental and useful technique in the construction of data processing system and can be effectively used in any other observatories, as well as in data processing system of Kyung Hee University.

• 인터넷정보학회논문지
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• 제25권2호
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• pp.11-19
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• 2024

This paper was studied abouta technology for detecting damage to temporary works equipment used in construction sites with explainable artificial intelligence (XAI). Temporary works equipment is mostly composed of steel or aluminum, and it is reused several times due to the characters of the materials in temporary works equipment. However, it sometimes causes accidents at construction sites by using low or decreased quality of temporary works equipment because the regulation and restriction of reuse in them is not strict. Currently, safety rules such as related government laws, standards, and regulations for quality control of temporary works equipment have not been established. Additionally, the inspection results were often different according to the inspector's level of training. To overcome these limitations, a method based with AI and image processing technology was developed. In addition, it was devised by applying explainableartificial intelligence (XAI) technology so that the inspector makes more exact decision with resultsin damage detect with image analysis by the XAI which is a developed AI model for analysis of temporary works equipment. In the experiments, temporary works equipment was photographed with a 4k-quality camera, and the learned artificial intelligence model was trained with 610 labelingdata, and the accuracy was tested by analyzing the image recording data of temporary works equipment. As a result, the accuracy of damage detect by the XAI was 95.0% for the training dataset, 92.0% for the validation dataset, and 90.0% for the test dataset. This was shown aboutthe reliability of the performance of the developed artificial intelligence. It was verified for usability of explainable artificial intelligence to detect damage in temporary works equipment by the experiments. However, to improve the level of commercial software, the XAI need to be trained more by real data set and the ability to detect damage has to be kept or increased when the real data set is applied.

• 한국측량학회지
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• 제35권2호
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• pp.75-80
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• 2017

Recently, there has been growing interest in spatial data that combines information and communication technology with smart cities. The high-precision LiDAR (Light Dectection and Ranging) equipment is mainly used to collect three-dimensional spatial data, and the acquired data is also used to model geographic features and to manage plant construction and cultural heritages which require precision. The LiDAR equipment can collect precise data, but also has limitations because they are expensive and take long time to collect data. On the other hand, in the field of computer vision, research is being conducted on the methods of acquiring image data and performing 3D reconstruction based on image data without expensive equipment. Thus, precise 3D spatial data can be constructed efficiently by collecting and processing image data using CCTVs which are installed as infrastructure facilities in smart cities. However, this method can have an accuracy problem compared to the existing equipment. In this study, experiments were conducted and the results were analyzed to increase the number of extracted matching points by applying the feature-based method and the area-based method in order to improve the precision of 3D spatial data built with image data acquired from stereo CCTVs. For techniques to extract matching points, SIFT algorithm and PATCH algorithm were used. If precise 3D reconstruction is possible using the image data from stereo CCTVs, it will be possible to collect 3D spatial data with low-cost equipment and to collect and build data in real time because image data can be easily acquired through the Web from smart-phones and drones.

• 정보보호학회논문지
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• 제26권4호
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• pp.1057-1071
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• 2016

무인항공기에 의한 사생활 침해는 신고를 필요로 하지 않는 소형 무인항공기에 장착된 영상정보처리기기로 인해 발생할 가능성이 크다. 본 논문에서는 무인항공기로부터의 사생활 보호를 위해 사생활 보호 관련 법령 - 개인정보보호법, 정보통신망법 - 등이 무인항공기에 장착된 영상정보처리기기의 이동성을 반영할 수 있도록 보완될 것을 제안한다. 이와 함께, 사생활 침해의 우려가 가장 큰 미신고 소형 무인항공기에 대한 규정을 항공관련 법령에 포함할 것을 제안한다. 또한 피촬영자의 무인항공기 인지 및 촬영된 영상정보에 대한 비식별화 조치 등의 기술적 대응 방안을 제안한다.

• Nuclear Engineering and Technology
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• 제53권1호
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• pp.294-303
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• 2021

Various types of sensors are used at industrial sites to measure vibration. With the increase in the diversity of vibration measurement methods, vibration monitoring methods using camera equipment have recently been introduced. However, owing to the physical limitations of the hardware, the measurement resolution is lower than that of conventional sensors, and real-time processing is difficult because of extensive image processing. As a result, most such methods in practice only monitor status trends. To address these disadvantages, a high-resolution vibration measurement method using image analysis of the edge region of the structure has been reported. While this method exhibits higher resolution than the existing vibration measurement technique using a camera, it requires significant amount of computation. In this study, a method is proposed for rapidly processing considerable amount of image data acquired from vision equipment, and measuring the vibration of structures with high resolution. The method is then verified through experiments. It was shown that the proposed method can fast measure vibrations of structures remotely.

• 한국공작기계학회논문집
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• 제16권3호
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• pp.15-22
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• 2007

An automatic measurement system which collects experimental data at an unmanned station where the networking to the internet could not be accessed was developed. With a Robo-rail accessing to the unmanned station, wireless local networking between server PC at the Rob-rail and client PC at the unmanned station is possible within 30 m from an access point equipment located at the unmanned station. An algorithm for transferring the data file which is saved in the client PC at the unmanned station to the server PC in the Robo-rail was proposed. IEEE-1394 camera was used to collect the data at the client PC. An extracting program from the IEEE-1394 captured images to character data and number data was developed using image processing technique, which drastically reduces the size of data file comparing to that of the raw image file.

• 핵의학기술
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• 제12권1호
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• pp.13-18
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• 2008

목적: 다양한 algorism에 의한 영상처리기법은 핵의학 영상을 결정짓는 중요한 부분을 차지하고 있다. 이에 새로운 영상처리기법인 SIEMENS (made by pixon)사의 Onco. flash processing reconstruction을 적용하여 기존의 영상처리기법을 이용한 영상과 비교 분석함으로써 그 임상적 유용성을 평가한다. 대상 및 방법: 1) Scan speed의 차이에 의한 whole body bone scan을 시행하고, raw data와 processing data의 imaeg quality를 비교 분석하여 상대 평가한다. 2) Bone static scan을 acquisition count를 달리하여 시행하고, raw data와 processing data의 image quality를 비교 분석하여 상대 평가한다. 3) 4 quadrant - bar phantom을 이용하여 raw data와 processing data와의 육안적 평가를 통한 image quality를 확인한다. 4) LSF을 통한 raw data와 processing data의 FWHM을 구하여 해상력 평가를 확인한다. 결과: 1) Whole body bone scan을 시행하여 본원 핵의학 판독의의 blinding test한 결과 scan speed 20 cm/min의 raw data와 30 cm/min의 processing data에는 임상 판독에 영향을 미칠 수준의 image quality 저하가 없었으나, 40 cm/min processing data는 영상 판독과 진단에 오류의 가능성을 배제 할 수 없는 image quality의 향상을 볼 수 없었다. 2) Bone static scan의 경우 200 kcts processing data는 200 kcts raw data보다 확실한 image quality의 향상을 가져왔으며 400 kcts raw data와 비교한 본원 핵의학 판독의 blinding test 결과 판독과 진단에 무리가 없을 수준의 유사한 image quality를 보였다. 3) 4 quadrant - bar phantom을 이용하여 raw data와 processing data와의 육안적 평가는 processing을 통한 image quality의 향상을 확인할 수 있었다. 4) LSF을 통한 raw data와 processing data의 FWHM 평가 결과, resolution의 뚜렷한 증가나 감소의 확인은 할 수 없었다. 이는 noise level의 감소와 high S/N ratio 때문이라 판단된다. 결론: 기존의 영상과 비교 분석하여 평가한 결과 Onco. flash processing reconstruction을 적용한 경우 일정 수준까지 뚜렷한 image quality의 향상을 보였으며, 이는 장비 가동률의 상승과 환자 대기일수의 단축 그리고 저선량 검사에 따른 방사선 피폭에 대한 적극적 방어의 관점에서 현재 임상 핵의학에 충분한 유용성과 타당성이 있을 것으로 사료된다.

• Journal of information and communication convergence engineering
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• 제19권1호
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• pp.54-60
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• 2021

Various digital devices were supplied throughout the Fourth Industrial Revolution. Accordingly, the importance of data processing has increased. Data processing significantly affects equipment reliability. Thus, the importance of data processing has increased, and various studies have been conducted on this topic. This study proposes a modified Gaussian filter algorithm based on a fuzzy membership function. The proposed algorithm calculates the Gaussian filter weight considering the standard deviation of the filtering mask and computes an estimate according to the fuzzy membership function. The final output is calculated by adding or subtracting the Gaussian filter output and estimate. To evaluate the proposed algorithm, simulations were conducted using existing additive white Gaussian noise removal algorithms. The proposed algorithm was then analyzed by comparing the peak signal-to-noise ratio and differential image. The simulation results show that the proposed algorithm has superior noise reduction performance and improved performance compared to the existing method.

• 한국인터넷방송통신학회논문지
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• 제19권6호
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• pp.9-13
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• 2019

본 논문에서는 IoT 기반 열상 센서와 영상 센서 일체형 IP CCTV 설계에 관하여 연구하였으며 Full HD IP 카메라 영상과 열상모듈에서 전송되어지는 열상 데이터를 동시에 인지하여 가공 및 전송 할 수 있는 모니터링 시스템에 사용할 수 있도록 하였다. 열상 센서에서 감지하는 신호를 디지털로 변환하여 영상에 중첩시켜 실제 주변 온도에 대한 정보를 영상과 함께 실시간 제공하고, 영상 카메라에 열상이 추가됨으로 온도 변화를 예측하여 기존 장비에서 불가능한 화재 예측이 가능하게 하였다. 따라서 열상 센서와 영상센서 일체형 감시 장비를 통하여 환경 모니터링 시스템에서 전송되는 온도 데이터와 영상 신호를 송신하여 모니터링 시스템에 적용 가능하도록 하였다.

• 융합정보논문지
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• 제11권12호
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• pp.30-38
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• 2021

본 논문에서는 열화상 이미지에서의 열 데이터 추출 및 해당 데이터를 사용한 발열 설비 탐지 향상 기법을 제안한다. 주요 목표는 열화상 이미지에서 바이트 단위로 데이터를 해석하여 열 데이터와 실화상 이미지를 추출하고 해당 이미지와 데이터를 합성한 합성 이미지를 딥러닝 모델에 적용하여 발열 설비의 탐지 정확도를 향상 시키는 것이다. 데이터는 한국수력원자력발전소 설비 데이터를 사용하였으며, 학습 모델로는 Faster-RCNN을 사용하여 각 데이터 그룹에 따른 딥러닝 탐지 성능을 비교 평가한다. 제안한 방식은 Average Precision 평가에서 기존 방식에 비해 평균 0.17 향상 되었다.본 연구는 이로서 국가 데이터 기반 열화상 데이터와 딥러닝 탐지의 접목을 시도하여 유효한 데이터 활용도 향상을 이루었다.