• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.6
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• pp.48-56
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• 1989

Contact-type linear image sensors for facsimile have been fabricated by means of rf glow discharge decomposition method of silane. The dependence of their electrical and optical properties on rf power, $SiH_4$ flow rate, ambient gas pressure, $H_2SiH_4$ ratio and substrate temperature are described. The a-Si:H monolayer demonstriated photosensitivity of 0.85 and $I_{ph}/I_d$ ratio of 100 unger 100 lux illumination. However, this monolayer has relatively high dark current due to carrier injection from both electrodes, resulting in low $I_{ph}/I_{dd}$ ratio. To suppress the dark current we have fabricated $SiO_2/i-a-Si:H/p-a-Si:H:B$ multilayer film with blocking structure. The photocurrent of this multilayer sensor with 6 V bias became saturated ar about 20nA under 10 lux illumination, while the dark current was less than 0.2 nA. Moreover, the spectral sensitivity of the multilayer film was enhanced for short wavelength visible region, compared with that of the a-Si:H monolayer. These results show that the fabricated photocon-ductive film can be used as the linear image sensor of the facsimile.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.4
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• pp.45-54
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• 2004

In this paper, a view point tracking system has been realized for outdoor augmented reality including broad area monitoring. Since the surroundings of the moving view point are changing, it is necessary to track the position and observation moment of the view point system for consistency between real and virtual images. For this reason, the GPS(Global Positioning System) is applied to the realized system for tracking the information on position and direction of the moving system. In addition, an optical position tracking system that is able to track view point in a limited area is used, because the local tracking system has to trace the image variation, seen to the observer in a moving vehicle, at a particular position and time. It was found that the realized outdoor augmented reality system, which combined the virtual information tracked in real time with the real image, can be very practical in various application area.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.39-47
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• 2017

The SAR payload of the KOMPSAT-5 is equipped with an X-band (9.66GHz) microwave-based sensor. Especially, since it has a fixed antenna that can be electronically steered with respect to the azimuth and elevation planes, various applications are expected. This study evaluates the production performance and the accuracy of the DEM by producing DEM using the HR and UH mode images of KOMPSAT-5. To evaluate the production performance of the DEM, the sensitivity of DEM was assessed through a baseline analysis and $2{\pi}$ ambiguity; it was found to have good production performance. In addition, to evaluate the accuracy of the produced DEM, 30 check points were compared with SRTM data. As a result, STDEV ${\pm}15-20m$ accuracy was obtained. If the accuracy of the DEM is improved by adjusting the parameters of the filtering method or phase unwrapping method in the future, it will be possible to widely use the KOMPSAT-5 image for environmental and disaster monitoring.

• Publications of The Korean Astronomical Society
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• v.21 no.2
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• pp.51-59
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• 2006

We have successfully developed the KASI (Korea Astronomy and Space Science Institute) Solar Imaging Spectrograph (KSIS), which has been originally upgraded from the KASI solar spectrograph that was able to record solar spectra for a given slit region and to inspect the response function of narrow band filters. A prototype KSIS was developed in 2004 by using a scanning mirror in front of the spectrograph slit and a SBIG ST-8XE CCD camera. Its main disadvantage is that it took a long time (about 13 minutes) to scan a whole active region. In this work, we have upgraded the KSIS by installing a much faster Dalsa 1M15 CCD camera, which gives a data acquisition time of about 2.5 minutes. The software for KSIS was also improved for the new CCD camera on the basis of component-based development method. We have successfully made a test observation for a simple and small active region (AR10910) using the improved KSIS system. Our observations show that H-alpha images for several wavelengths have typical features in a sunspot as well as a H-alpha centerline image is quite similar to a BBSO H-alpha image, demonstrating the capability of the KSIS system.

• Journal of Powder Materials
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• v.17 no.1
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• pp.13-22
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• 2010

The unique features of spark plasma sintering process are the possibilities of a very fast heating rate and a short holding time to obtain fully dense materials. $\beta$-SiC powder with 0, 2, 6, 10 wt% of $\alpha$-SiC particles (seeds) and 4 wt% of Al-B-C (sintering aids) were spark plasma sintered at $1700-1850^{\circ}C$ for 10 min. The heating rate, applied pressure and sintering atmosphere were kept at $100^{\circ}C/min$, 40 MPa and a flowing Ar gas (500 CC/min). Microstructural development of SiC as function of seed content and temperature during spark plasma sintering was investigated quantitatively and statistically using image analysis. Quantitative image analyses on the sintered SiC ceramics were conducted on the grain size, aspect ratio and grain size distribution of SiC. The microstructure of SiC sintered up to $1700^{\circ}C$ consisted of equiaxed grains. In contrast, the growth of large elongated SiC grains in small matrix grains was shown in sintered bodies at $1750^{\circ}C$ and the plate-like grains interlocking microstructure had been developed by increasing sintering temperature. The introduction of $\alpha$-SiC seeds into $\beta$-SiC accelerated the grain growth of elongated grains during sintering, resulting in the plate-like grains interlocking microstructure. In the $\alpha$-SiC seeds added in $\beta$-SiC, the rate of grain growth decreased with $\alpha$-SiC seed content, however, bulk density and aspect ratio of grains in sintered body increased.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.1 no.1
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• pp.23-26
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• 2000

In spot welded joint. Electronic Speckle Pattern Interferometry(ESPI) method using the Model 95 Ar laser a video system and an image processor was applied to measure the stress Unlike traditional strain gauges or Moire method, ESPI method has no special surface preparation or attachments and can be measured in-plane displacement with non-contact and real time. In this experiment, specimens are loaded in parallel with a load cell. The specimens are made of the cold rolled steel sheet with 1mm thickness, are attached strain. gauges. This study Provides an example of how ESPI has been used to measure stress and strain inspecimen. The results measured by ESPI are compared with the data which was measured by strain gauge method under tensile testing.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.5
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• pp.73-81
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• 2020

One of the most important vegetables consumed in Korea, chili peppers (Capsicum annuum) are widely cultivated around the world. Chili peppers have been severely damaged by anthracnose during their growth, so it is important to study prevention and resistance varieties. K1 anthracnose was inoculated against four cultivar of chili peppers that are resistant to anthracnose and one cultivar that is sensitive. The area of the disease that appeared over time was photographed and quantified through the program was analyzed. Through the ratio of the area of chili pepper fruit and the area of the bottle, the sensitive variety An-S showed weak reactions to anthracnose with about 40%, the resistant variety An-12R (23%), An-Tan (21%), and An-9R (19%), and PBC81 showed a strong response to anthracnose with about 11%. These quantitative value can be used as a basis for comparison in conducting resistance studies for new varieties.

• The Journal of Bigdata
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• v.3 no.2
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• pp.113-121
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• 2018

In this study, an augmented reality(AR)-based information management system for agricultural facility is proposed. Using a variety of sensed data transmitted by Lora-based wireless networks deployed at the agricultural facility, this system is capable of augmenting the sensed data and displaying them on the user's smartphone screen to provide visualized information to user. When users point their smartphone camera to the agricultural facility, the environment information collected from numerous sensors installed at the facility would be visualized and appear on the screen. Unlike traditional system which requires user to search a specific facility and then select sensor(s) to obtain the environment information, the proposed system shows the information on smartphone screen by augmenting it with real image captured by camera without doing a series of time-taking selection process. Since the way of acquiring information is through image or video, this system contributes to convenient monitoring and efficient management for agricultural facility.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.341-350
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• 2022

In this paper, we propose a deep learning based on-device augmented reality (AR) system in which multiple input images are used to implement the correct occlusion in a real environment. The proposed system is composed of three technical steps; camera pose estimation, depth estimation, and object augmentation. Each step employs various mobile frameworks to optimize the processing on the on-device environment. Firstly, in the camera pose estimation stage, the massive computation involved in feature extraction is parallelized using OpenCL which is the GPU parallelization framework. Next, in depth estimation, monocular and multiple image-based depth image inference is accelerated using the mobile deep learning framework, i.e. TensorFlow Lite. Finally, object augmentation and occlusion handling are performed on the OpenGL ES mobile graphics framework. The proposed augmented reality system is implemented as an application in the Android environment. We evaluate the performance of the proposed system in terms of augmentation accuracy and the processing time in the mobile as well as PC environments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.1-8
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• 2022

Recently, Google MedeiaPipe presents a novel approach for neural network-based hair segmentation from a single camera input specifically designed for real-time, mobile application. Though neural network related to hair segmentation is relatively small size, it produces a high-quality hair segmentation mask that is well suited for AR effects such as a realistic hair recoloring. However, it has undesirable segmentation effects according to hair styles or in case of containing noises and holes. In this study, the energy function of the test image is constructed according to the estimated prior distributions of hair location and hair color likelihood function. It is further optimized according to graph cuts algorithm and initial hair region is obtained. Finally, clustering algorithm and image post-processing techniques are applied to the initial hair region so that the final hair region can be segmented precisely. The proposed method is applied to MediaPipe hair segmentation pipeline.