• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1096-1098
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• 2003

SBC(Single Board Computer) is being developed for MSC(Multi-Spectral Camera) on KOMPSAT-2(Korea Multi-Purpose Satellite). SBC controls all the units of MSC system and gets commands and sends telemetry to and from spacecraft bus via 1553 communication channel. Due to the fact that SBC does very important roles for MSC system operation and SBC operates with 100% duty cycle, SBC is designed to have high reliability. SBC which has Intel 80486 as a main processor includes eight serial communication channels, one mil-std-1553 interface channel and several discrete interfaces. SBC incorporates 2Mbyte radiation hardened SRAM(Static Random Access Memory) and 1Mbyte flash memory. There are also PIC(Programmable Interrupt Controller), counter, WDT(Watch Dog Timer) in the SBC. In this paper, the design result of the SBC is presented.

• The Korean Journal of Nuclear Medicine
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• v.39 no.3
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• pp.151-162
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• 2005

Hemangioma is the most common benign tumor of the liver, with a prevalence estimated as high as 7%. Tc-99m red blood cell (RBC) hepatic blood pool scan with single photon omission computed tomography (SPECT) imaging is extremely useful for the confirmation or exclusion of hepatic hemangiomas. The classic finding of absent or decreased perfusion and increased blood pooling ("perfusion/blood pool mismatch") is the key diagnostic element in the diagnosis of hemangiomas. The combination of early arterial flow and delayed blood pooling ("perfusion/blood pool match") is shown uncommonly. In giant hemangioma, filling with radioactivity appears first in the periphery, with progressive central fill-in on sequential RBC blood pool scan. However, the reverse filling pattern, which begins first in the center with progressive peripheral filling, is also rarely seen. Studies with false-positive blood pooling have been reported infrequently in nonhemangiomas, including hemangiosarcoma, hepatocellular carcinoma, hepatic adenoma, and metastatic carcinomas (adenocarcinoma of the colon, small cell carcinoma of the lung, neruroendocrine carcinoma). False-negative results have been also reported rarely except for small hemagniomas that are below the limits of spatial resolution of gamma camera.

• Journal of KIISE
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• v.42 no.8
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• pp.990-997
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• 2015

Panoramic image creation has been extensively studied. Existing methods use customized hardware, or apply post-processing methods to seamlessly stitch images. These result in an increase in either cost or complexity. In addition, images can only be stitched under certain conditions such as existence of characteristic points of the images. This paper proposes a low cost and easy-to-use system that produces realtime panoramic video. We use an off-the-shelf embedded platform to capture multiple images, and these are then transmitted to a server in a compressed format to be merged into a single panoramic video. Finally, we analyze the performance of the implemented system by measuring time to successfully create the panoramic image.

• Journal of Korea Multimedia Society
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• v.17 no.5
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• pp.556-565
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• 2014

This paper proposes a method to track object of real-time video transferred through single web-camera and to recognize risk-situation and human actions. The proposed method recognizes human basic actions that human can do in daily life and finds risk-situation such as faint and falling down to classify usual action and risk-situation. The proposed method models the background, obtains the difference image between input image and the modeled background image, extracts human object from input image, tracts object's motion and recognizes human actions. Tracking object uses the moment information of extracting object and the characteristic of object's recognition is moment's change and ratio of object's size between frames. Actions classified are four actions of walking, waling diagonally, sitting down, standing up among the most actions human do in daily life and suddenly falling down is classified into risk-situation. To test the proposed method, we applied it for eight participants from a video of a web-cam, classify human action and recognize risk-situation. The test result showed more than 97 percent recognition rate for each action and 100 percent recognition rate for risk-situation by the proposed method.

• International Journal of Air-Conditioning and Refrigeration
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• v.13 no.4
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• pp.196-205
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• 2005

In this paper, recent research trend on heat transfer in impinging jet is reviewed. We focused on submerged jet that air issued into air or liquid issued into liquid. To control and enhance the heat transfer in single jet, researchers have performed a lot of experiments by considering the nozzle geometry, impinging surface and active method such as jet vibration, secondary injection and suction flow. The studies on multiple jet have been mainly focused on finding out the optimum condition and on investigating many different factors concerned with application condition (crossflow, rotation and geometry etc.) and combined techniques (rib turbulator, pin fin, dimple and effusion hole etc.). All most experiments showed the detailed heat transfer data by using liquid crystal method, infrared camera technique and naphthalene sublimation method. Many numerical calculations have been performed to investigate the flow and heat transfer characteristics in laminar jet region. Various turbulence models such as $k-\varepsilon-\bar{\nu^2}$, modified $k-\varepsilon-f_{\mu}$ were applied to the calculation for turbulent jet and the predicted results showed a good agreement with the experimental data. Although a lot of studies on impinging jet have performed consistently up to recently, further studies are still required to understand the flow and heat transfer characteristics more accurately, and to give a guideline for optimum impinging jet design in various applications.

• Current Optics and Photonics
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• v.5 no.5
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• pp.514-523
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• 2021

Methods for absolute depth estimation have received lots of interest, and most algorithms are concerned about how to minimize the difference between an input defocused image and an estimated defocused image. These approaches may increase the complexity of the algorithms to calculate the defocused image from the estimation of the focused image. In this paper, we present a new method to recover depth of scene based on a sharpness-assessment algorithm. The proposed algorithm estimates the depth of scene by calculating the sharpness of deconvolved images with a specific point-spread function (PSF). While most depth estimation studies evaluate depth of the scene only behind a focal plane, the proposed method evaluates a broad depth range both nearer and farther than the focal plane. This is accomplished using an asymmetric aperture, so the PSF at a position nearer than the focal plane is different from that at a position farther than the focal plane. From the image taken with a focal plane of 160 cm, the depth of object over the broad range from 60 to 350 cm is estimated at 10 cm resolution. With an asymmetric aperture, we demonstrate the feasibility of the sharpness-assessment algorithm to recover absolute depth of scene from a single defocused image.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.45-53
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• 2019

RGB-D SLAM (Simultaneous Localization and Mapping) refers to the technology of using deep camera as a visual sensor for SLAM. In view of the disadvantages of high cost and indefinite scale in the construction of maps for laser sensors and traditional single and binocular cameras, a method for creating three-dimensional map of indoor environment with deep environment data combined with RGB-D SLAM scheme is studied. The method uses a mobile robot system equipped with a consumer-grade RGB-D sensor (Kinect) to acquire depth data, and then creates indoor three-dimensional point cloud maps in real time through key technologies such as positioning point generation, closed-loop detection, and map construction. The actual field experiment results show that the average error of the point cloud map created by the algorithm is 0.0045m, which ensures the stability of the construction using deep data and can accurately create real-time three-dimensional maps of indoor unknown environment.

• Smart Structures and Systems
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• v.32 no.2
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• pp.123-133
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• 2023

This paper proposes a thermography-based coating thickness estimation method for steel structures using model-agnostic meta-learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured using an infrared (IR) camera. The measured heat responses are then analyzed using model-agnostic meta-learning to estimate the coating thickness, which is visualized throughout the inspection surface of the steel structure. Current coating thickness estimation methods rely on point measurement and their inspection area is limited to a single point, whereas the proposed method can inspect a larger area with higher accuracy. In contrast to previous ANN-based methods, which require a large amount of data for training and validation, the proposed method can estimate the coating thickness using only 10- pixel points for each material. In addition, the proposed model has broader applicability than previous methods, allowing it to be applied to various materials after meta-training. The performance of the proposed method was validated using laboratory-scale and field tests with different coating materials; the results demonstrated that the error of the proposed method was less than 5% when estimating coating thicknesses ranging from 40 to 500 ㎛.

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.124-130
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• 2023

Implementing flexible production systems in domestic and foreign automotive design parts assembly has increased demand for automation and power reduction. Consequently, transition to a hybrid production method is observed where multiple vehicles are assembled in a single assembly line. Multiple robots, 3D vision sensors, mounting positions, and correction software have complex configurations in the automotive glass mounting system. Hence, automation is required owing to significant difficulty in the assembly process of automobile parts. This study presents a primer lighting and inspection algorithm that is robust to the assembly environment of real automotive design parts using high power 'ㄷ'-shaped LED inclined lighting. Furthermore, a 2D camera was developed in the primer coating inspection system-the core technology of the glass mounting system. A primer application demo line applicable to the actual automobile production line was established using the proposed high power lighting and algorithm. Furthermore, application inspection performance was verified using this demo system. Experimental results verified that the performance of the proposed system exceeded the level required to satisfy the automobile requirements.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.303-304
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• 2021

It is an important issue to detect automatically whether a mask is worn or not for corona prevention. It is known that mask wearing detection can be solved by learning the face data set. However, the search for whether a person is wearing a mask can be detected in a simpler way using OpenCV. In this paper, we describe that it is possible to easily detect whether a single person is wearing a mask or not with a general PC camera using OpenCV learning data results and simple OpenCV functions. Through experiments, the proposed method was shown to be effective.