• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.989-1006
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• 2020

Building change monitoring based on building detection is one of the most important fields in terms of monitoring artificial structures using high-resolution multi-temporal images such as CAS500-1 and 2, which are scheduled to be launched. However, not only the various shapes and sizes of buildings located on the surface of the Earth, but also the shadows or trees around them make it difficult to detect the buildings accurately. Also, a large number of misdetection are caused by relief displacement according to the azimuth and elevation angles of the platform. In this study, object-based building detection was performed using the azimuth angle of the Sun and the corresponding main direction of shadows to improve the results of building change detection. After that, the platform's azimuth and elevation angles were used to detect changed buildings. The object-based segmentation was performed on a high-resolution imagery, and then shadow objects were classified through the shadow intensity, and feature information such as rectangular fit, Gray-Level Co-occurrence Matrix (GLCM) homogeneity and area of each object were calculated for building candidate detection. Then, the final buildings were detected using the direction and distance relationship between the center of building candidate object and its shadow according to the azimuth angle of the Sun. A total of three methods were proposed for the building change detection between building objects detected in each image: simple overlay between objects, comparison of the object sizes according to the elevation angle of the platform, and consideration of direction between objects according to the azimuth angle of the platform. In this study, residential area was selected as study area using high-resolution imagery acquired from KOMPSAT-3 and Unmanned Aerial Vehicle (UAV). Experimental results have shown that F1-scores of building detection results detected using feature information were 0.488 and 0.696 respectively in KOMPSAT-3 image and UAV image, whereas F1-scores of building detection results considering shadows were 0.876 and 0.867, respectively, indicating that the accuracy of building detection method considering shadows is higher. Also among the three proposed building change detection methods, the F1-score of the consideration of direction between objects according to the azimuth angles was the highest at 0.891.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.75-81
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• 2013

We presents a novel (2, 2) secret sharing (SS) scheme for all grayscale images. Generally, a secret image is distribute more than two shadow images, which are dealt out among participants. In order to find out secret image, participants print shadow images to transparent papers. Then, a secret image will appear as stacking transparent papers. The secret sharing scheme in this paper distribute secret image into natural grayscale images using multiplexer and data hiding scheme. After then, two participant have two shadow images respectively. The merit of the proposed scheme is that shadow images have small loss in aspect of the quality with steganographic features. Therefore, the proposed secret sharing scheme in this paper is not easily detected by attackers. The experiment result verified that the proposed scheme, obviously outperforms previous SS schemes.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.520-523
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• 2022

일본 우주항공연구개발기구(Japan Aerospace Exploration Agency, JAXA)는 2007년부터 2017년까지 달 탐사선 셀레네(Selenological and Engineering Explorer, SelEnE)가 관측한 데이터를 수집하고, 연구했다. JAXA는 지구 상층 대기에 존재하는 산소가 자기장의 꼬리 부분에 실려 달로 이동한다는 사실을 발견했다. 하지만 이 연구는 아직 진행 중이며 달의 산화 과정 규명에 추가 연구가 필요하다. 본 논문에서는 생성적 적대 신경망(Generative Adversarial Networks, GAN)으로 달 분화구의 영구 그림자 영역을 제거하고, 물과 얼음을 발견하여 선행 연구의 완성도를 향상하고자 한다. 실험에 사용할 모델은 CIPS(Conditionally Independent Pixel Synthesis)다. CIPS는 실제 같은 영상을 고해상도로 합성한다. 합성할 데이터의 최적인 가중치 초기화 및 파라미터 갱신 방법, 활성 함수 조합은 실험을 통해 확인한다. 필요에 따라 앙상블 학습을 할 수도 있다. 성능평가는 FID(Frechet Inception Distance), 정밀도, 재현율을 사용한다. 제안한 방법은 진행 중인 연구의 시간과 비용을 절약하고, 인과관계를 더욱 명확히 밝히는 데 도움 될 수 있다고 사료된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.556-563
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• 2020

Most of a BIPVS (Building Integrated Photovoltaic System) is installed on the rooftop or wall of a building. Therefore, the main factor to consider for selecting the installation site is the shadow effects produced by the surrounding buildings. On the other hand, when the photovoltaic was installed on soundproof walls, shadow effects were produced by not only surrounding buildings but also the surrounding trees. Therefore, a different data model and algorithm with the BIPVS case are essential for proper installation sites selection of a SIPVS (Soundproof wall Integrated Photovoltaic System). This paper deals with the DSM (Digital Surface Model)-based proper installation site analysis for SIPVS. First, the solar incident and altitude angles of the installation candidate sites (solar panel) during the year were calculated. Second, the shadow effects (shadowed or unshadowed) were determined for the candidate sites at each time with the DSM. Third, the amount of solar radiation was calculated with the incident angle for the candidate sites at an unshadowed period. The proper installation site of the SIPVS could then be selected by comparing the accumulated annual solar radiation for each candidate. The proposed algorithm was implemented as a prototype (Java program). From the experiment, the order of the installation suitability was determined among the nine candidates. The proposed algorithm could be used for proper BIPVS installation site analysis aimed at the lower part of a building and calculation of the expected power production.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.59-67
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• 2009

In wireless sensor networks (WSNs), geographic greedy forwarding fails to move a packet further towards its destination if the sender does not have any closer node to the destination in its one hop transmission region. In this paper, we propose a enhanced geographic routing, called CGR(Cost based Geographic Routing) for efficient data delivery against void problem environment. CGR first establishes Shadow Bound Region and then accomplishes Renewing Cost Function Algorithm for effective greedy forwarding data delivery. Our simulation results show significant improvements compared with existing schemes in terms of routing path length, success delivery ratio and energy efficiency.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.1277-1282
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• 2006

본 논문에서는 배경과 오브젝트 합성 시 사실적인 그림자 효과를 표현하기 위해 HDR 영상을 기반으로 한 소수의 방향성 광원을 추정하는 기법을 제안한다. 실 세계 정보를 모두 포함하는HDR 영상을 가시화 하기 위해 톤 맵핑(tone mapping)하여 그 영상으로부터 광원의 위치가 되는 밝은 영역들을 찾아내고 그 위치들로부터 방향성 광원을 추정한다. 카메라의 노출시간을 짧게 하여 촬영한 영상에서 나타나는 부분을 실제 광원이 위치하는 부분으로 볼 수 있으므로 톤 맵핑한 영상을 이미지 프로세싱을 거쳐 노출 시간을 짧게 하여 촬영한 영상과 비슷한 결과를 얻을 수 있도록 한 후 밝은 영역만 표현 되도록 한다. 전 처리를 거친 영상을 기반으로 밝은 영역을 추정하기 때문에 보다 정확한 광원의 위치 추정이 가능하며, 추정된 밝은 영역과 일치하는 HDR 영상의 데이터를 사용하기 때문에 정확한 광원의 위치와 데이터를 얻을 수 있다. 또한 추정된 광원은 실제 렌더링에 곧바로 사용이 가능하며, 이를 통해 사실적인 shadowing 효과를 얻을 수 있다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5D
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• pp.635-644
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• 2009

Image processing technique in the outdoor environment is very sensitive, and it tends to lose a lot of accuracy when it rapidly changes by outdoor environment. Therefore, in order to calculate accurate traffic information using the traffic monitoring system, we must resolve removing shadow in transition time, Distortion by the vehicle headlights at night, noise of rain, snow, and fog, and occlusion. In the research, we developed a system to calibrate the amount of traffic, speed, and time occupancy by using image processing technique in a variety of outdoor environments change. This system were tested under outdoor environments at the Gonjiam test site, which is managed by Korea Institute of Construction Technology (www.kict.re.kr) for testing performance. We evaluated the performance of traffic information, volume counts, speed, and occupancy time, with 4 lanes (2 lanes are upstream and the rests are downstream) from the 16th to 18th December, 2008. The evaluation method performed as based on the standard data is a radar detection compared to calculated data using image processing technique. The System evaluation results showed that the amount of traffic, speed, and time occupancy in period (day, night, sunrise, sunset) are approximately 92-97% accuracy when these data compared to the standard data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.2
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• pp.287-298
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• 1997

The main object of this study was to prove the effectiveness of satellite image data for extraction of the Matsucoccus Thenbergianae Miller ビt Park damaged area. The effectiveness of extraction of damaged area was improved by using the BRCT(Backwards radiance correction transformation) with DEM for normalization of topographic effects. The surface analysis of the extracted damaged area was revealed that the damage was started at south-west slope with the aspect of 7 to 18 degrees, and 50% to 70% of the highest altitude mountains. The direction of damage attached by the Matsucoccus Thunbergianae Miller et Park was able to predict through the analysis of periodical of years' images

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.1-9
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• 2020

A smart factory is a key industrial application introduced by the 4^th industrial revolution. The automatic guided vehicle (AGV) is one of the technology realizing smart factory, but the development cost is high due to its early stage of technology. Although developing a low-cost AGV requires a lot of data, it has limited data acquisition capability because of the limited storage and the AGV movement. Hence, we propose a development environment using Bluetooth to collect data and design a lane detector. The proposed lane detector shows a high lane detection ratio regardless of light variation and a shade.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.139-145
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• 2006

The advantage of the lidar data is in fast acquisition and process time as well as in high accuracy and high point density. However lidar data itself is difficult to classify the earth surface because lidar data is in the form of irregularly distributed point clouds. In this study, we investigated land cover classification using both lidar data and optical image through a supervised classification method. Firstly, we generated 1m grid DSM and DEM image and then nDSM was produced by using DSM and DEM. In addition, we had made intensity image using the intensity value of lidar data. As for optical images, the red, blue, green band of CCD image are used. Moreover, a NDVI image using a red band of the CCD image and infrared band of IKONOS image is generated. The experimental results showed that land cover classification with lidar data and optical image together could reach to the accuracy of 74.0%. To improve classification accuracy, we further performed re-classification of shadow area and water body as well as forest and building area. The final classification accuracy was 81.8%.