• Journal of Ocean Engineering and Technology
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• v.33 no.3
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• pp.289-299
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• 2019

Various sizes of ROVs are being utilized in offshore industrial, scientific, and military applications all around the world. Because of innovative developments in science and technology, image acquisition devices such as sonar devices and cameras have been reduced in size and their performance has been improved. Thus, we can expect better accuracy and higher resolution even in the case of exploration using a small ROV. The purpose of this paper is to prepare a standard procedure for the identification of unidentified hazardous materials found during the National Oceanographic Survey. In this paper, we propose an IDEF (Integrated DEFinition) method modeling technique to identify unidentified targets using a small ROV. In accordance with the proposed procedure, an ROV survey was carried out on target No.16 with a four-ton-class fishing boat as a support vessel on September 18th of 2018 in the sea near Daebu Island. Unidentified targets, which were not known by the multi-beam data obtained from the ship, could be identified as concrete pipes by analyzing the HD camera and high-resolution sonar images acquired by the ROV. The whole proposed procedure could be verified, and the survey with the small ROV required about 10 days to identify the target in one place.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.93-98
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• 2023

As semiconductor devices become highly integrated and process difficulty increases, the need for highly sensitive sensors that can detect micro leaks is increasing. However, the noise contained in the CCD sensor itself acts as an obstacle to detecting fine leaks. In this study, integration time was changed for each condition, the sensor was cooled to 0℃, and the dark voltage level was measured to confirm through experiment the characteristics of the temporal noise included in the CCD sensor, a component of OES (Optical Emission Spectroscopy). When integration time was reduced from 30msec to 10msec, the dark voltage level decreased by about 20.5 % from an average of 151.5mV to 120.5mV. In the case of cooling device, Peltier elements were selected because of their simple structure and small size. During temperature cooling, the target temperature was controlled to within ±0.5℃ through PID control. When cooled from 20℃ to 0℃ using this cooling device, it was confirmed that the dark voltage level decreased by about 7% from an average of 147.0mV to 137.0mV.

• Journal of the Korean Society of Radiology
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• v.13 no.1
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• pp.111-118
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• 2019

Chest digital tomosynthesis has become a practical imaging modality because it can solve the problem of anatomy overlapping in conventional chest radiography. However, because of both limited scan angle and finite-size detector, a portion of chest cannot be represented in some or all of the projection. These bring a discontinuity in intensity across the field of view boundaries in the reconstructed slices, which we refer to as the truncation artifacts. The purpose of this study was to reduce truncation artifacts using a weighted normalization approach and to investigate the performance of this approach for our prototype chest digital tomosynthesis system. The system source-to-image distance was 1100 mm, and the center of rotation of X-ray source was located on 100 mm above the detector surface. After obtaining 41 projection views with ${\pm}20^{\circ}$ degrees, tomosynthesis slices were reconstructed with the filtered back projection algorithm. For quantitative evaluation, peak signal to noise ratio and structure similarity index values were evaluated after reconstructing reference image using simulation, and mean value of specific direction values was evaluated using real data. Simulation results showed that the peak signal to noise ratio and structure similarity index was improved respectively. In the case of the experimental results showed that the effect of artifact in the mean value of specific direction of the reconstructed image was reduced. In conclusion, the weighted normalization method improves the quality of image by reducing truncation artifacts. These results suggested that weighted normalization method could improve the image quality of chest digital tomosynthesis.

• Progress in Medical Physics
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• v.19 no.4
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• pp.291-297
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• 2008

The purpose of this study is to optimize a parallel-hole collimator for small gamma camera having the pixellated crystal array and evaluate the effect of crystal-collimator misalignment on the image quality using a simulation tool GATE (Geant4 Application for Tomographic Emission). The spatial resolution and sensitivity were measured for the various size of hexagonal-hole and matched square-hole collimators with a Tc-99m point source and the uniformity of flood image was estimated as a function of the angle between crystal array and collimator by misalignment. The results showed that the spatial resolution and sensitivity were greatly improved by using the matched collimator and the uniformity was reduced by crystal-collimator misalignment.

• Geophysics and Geophysical Exploration
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• v.20 no.3
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• pp.176-184
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• 2017

To interpret the seismic image precisely, random noises should be suppressed and the continuity of the image should be enhanced by using the appropriate smoothing techniques. Structure-Oriented Filter-Edge Preserving (SOF-EP) technique is one of the methods, that have been actively researched and used until now, to efficiently smooth seismic data while preserving the continuity of signal. This technique is based on the principle that diffusion occurs from large amplitude to small one. In a continuous structure such as a horizontal layer, diffusion or smoothing is operated along the layer, thereby increasing the continuity of layers and eliminating random noise. In addition, diffusion or smoothing across boundaries at discontinuous structures such as faults can be avoided by employing the continuity decision factor. Accordingly, the precision of the smoothing technique can be improved. However, in the case of the structure-oriented semblance technique, which has been used to calculate the continuity factor, it takes lots of time depending on the size of the filter and data. In this study, we first implemented the SOF-EP method and confirmed its effectiveness by applying it step by step to the field data. Next, we proposed and applied the corner response method which can efficiently calculate the continuity decision factor instead of structure-oriented semblance. As a result, we could confirm that the computation time can be reduced by about 6,000 times or more by applying the corner response method.

• Journal of the Korean Society of Radiology
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• v.8 no.5
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• pp.225-230
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• 2014

Assessments of medical image was improved in accordance with development of medical imaging systems. One of them is edge method to determining MTF(Modulation Transfer Function) based on the Fujita method. Fujita was reduced sampling interval used slightly angulated slit to the direction of pixel array and composited finely sampled LSF to determine presampling MTF. In this study, we investigate the effect of sampling interval on the MTF under a digital imaging system by changing wire angle. The wire method was equivalent to the slit method except signal appearance. A Simens's MAMMOMAT Inspiration with $0.085{\times}0.085mm^2$ pixel size made by amorphous selenium was used and 96% accuracy on MTF in twice sampling interval compared with Fujita was obtained. However, three times of sampling interval showed 93% accuracy on 50% of MTF and 85% accuracy on 10% of MTF.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.786-792
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• 2010

This paper presents a real-time lane detection method which can accurately find the lane-mark boundaries in complex road environment. Unlike many existing methods that pay much attention on the post-processing stage to fit lane-mark position among a great deal of outliers, the proposed method aims at removing those outliers as much as possible at feature extraction stage, so that the searching space at post-processing stage can be greatly reduced. To achieve this goal, a grid-based morphology operation is firstly used to generate the regions of interest (ROI) dynamically, in which a directional edge-linking algorithm with directional edge-gap closing is proposed to link edge-pixels into edge-links which lie in the valid directions, these directional edge-links are then grouped into pairs by checking the valid lane-mark width at certain height of the image. Finally, lane-mark colors are checked inside edge-link pairs in the YUV color space, and lane-mark types are estimated employing a Bayesian probability model. Experimental results show that the proposed method is effective in identifying lane-mark edges among heavy clutter edges in complex road environment, and the whole algorithm can achieve an accuracy rate around 92% at an average speed of 10ms/frame at the image size of $320{\times}240$.

• Journal of the Korean Society of Radiology
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• v.13 no.6
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• pp.825-830
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• 2019

A detector module measuring a depth of interaction was developed using silicon photomultiplier (SiPM) and two layers of scintillation crystal array treated with multiple reflectors. When reconstructing an image based on a signal obtained by using different types of reflector of each layer, the interaction positions of scintillation pixels and gamma rays could be tracked by utilizing the feature that all scintillation pixels were recorded at different positions. The bottom layer uses a specular reflector, and the top layer uses a diffuse reflector to differently process the size of the signal obtained from the SiPM. The optical grease was used to recude the sharp refractive index change between the layers of scintillator and the SiPM. The signals obtained from the 16 SiPMs were reduced to four signals using the Anger equations, and the images were reconstructed using them. All the scintillation pixels composed of the two layers appeared in the reconstructed image, which distinguished the layer where the scintillation pixels and gamma rays interacted. If the detectors, which measure the interaction depth of two layers using different reflectors, will be applied to preclinical positron emission tomography, the degradation of spatial resolution appearing outside the field of interest could be solved.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.11-17
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• 2022

In this paper, a model that can increase the efficiency of work in arranging interior furniture by applying augmented reality technology was studied. In the existing system to which augmented reality is currently applied, there is a problem in that information is limitedly provided depending on the size and nature of the company's product when outputting the image of furniture. To solve this problem, this paper presents an AR labeling algorithm. The AR labeling algorithm extracts feature points from the captured images and builds a database including indoor location information. A method of detecting and learning the location data of furniture in an indoor space was adopted using the CNN technique. Through the learned result, it is confirmed that the error between the indoor location and the location shown by learning can be significantly reduced. In addition, a study was conducted to allow users to easily place desired furniture through augmented reality by receiving detailed information about furniture along with accurate image extraction of furniture. As a result of the study, the accuracy and loss rate of the model were found to be 99% and 0.026, indicating the significance of this study by securing reliability. The results of this study are expected to satisfy consumers' satisfaction and purchase desires by accurately arranging desired furniture indoors through the design and implementation of AR labels.

• Journal of Industrial Convergence
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• v.20 no.12
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• pp.195-202
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• 2022

Underground Geospatial Information Map Management System(UGIMMS) integrates various underground facilities in the underground space into 3D mesh data, and supports to check the 3D image and location of the underground facilities in the mobile app. However, there is a problem that it takes a long time to run in the app because various underground facilities can exist in some areas executed by the app and can be seen layer by layer. In this paper, we propose a deep learning-based K-means vertex clustering algorithm as a method to reduce the execution time in the app by reducing the size of the data by reducing the number of vertices in the 3D mesh data within the range that does not cause a problem in visibility. First, our proposed method obtains refined vertex feature information through a deep learning encoder-decoder based model. And second, the method was simplified by grouping similar vertices through K-means vertex clustering using feature information. As a result of the experiment, when the vertices of various underground facilities were reduced by 30% with the proposed method, the 3D image model was slightly deformed, but there was no missing part, so there was no problem in checking it in the app.