• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.661-666
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• 2007

최근들어 제품을 개발하는 과정 중, 디자이너와 개발자, 의사 결정권자들이 FEM, CFD 시뮬레이션 결과를 리뷰할 때에 가상현실기술을 도입하는 사례가 늘고 있다. 몰입감을 높여주는 가상현실환경은 모델에 대한 해석 결과물을 정확하고 효과적으로 분석할 수 있도록 돕는다. 데이터의 실제 크기와 같게 혹은 그보다 더 크고 자세한 이미지를 제공하는 가상현실 몰입환경은 사용자가 데스크탑 환경만을 사용할 때 경험할 수 없는 높은 사실감을 제공함으로써 사용자에게 시각적인 만족감을 줄 수 있다. 하지만 데스크탑 환경에 비해 해상도가 낮고, 어두운 곳에서 스테레오 안경이나 HMD(Head Mounted Display), Data glove등을 착용해야 하는 불편함과 멀미, 시각적인 피로, 방향감각 상실로 대표되는 가상멀미 등으로 인해 장시간 사용에 어려움이 있다. 데스트탑 환경에서의 데이터 리뷰는 고해상도 이미지 분석은 가능하지만, 입체감이 떨어지기 때문에 리뷰 데이터의 실제감이 떨어진다. 이와 같은 문제점들을 보완하기 위해서 본 논문에서는 데스크탑 환경과 가상현실 환경 간의 협업이 가능한 FEM/CFD 가시화 시스템을 제시한다. 본 시스템은 가상현실 몰입환경에서 해석 데이터를 단순히 가시화하는 것뿐만이 아니라, 데스크탑 시스템과 동일한 3D 인터페이스 구조를 제공한다. 따라서, 해석 결과 분석을 위한 동일한 post-processing 작업이 네트워크로 연결된 원격 공간의 사용자들이 사용하는 시스템들 사이에서 실시간으로 진행될 수 있다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.45-50
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• 2010

An image interpolation is a technique to use for enhancement of image resolution, it have two problems which are image quality degradation of the interpolated result image and high computation complexity. In this paper, to solve the problem, we propose an image interpolation algorithm using loss information estimation and implement the proposed method on portable device. From reduction image of obtained low resolution image, the proposed method can computes error to use image interpolated and estimate loss information by interpolation of the computed error. The estimated loss information is added to interpolated high resolution image with weight factor. We verified that the proposed method has improved FSNR as 2dB than conventional algorithms by experiments. Also, we implemented the proposed method on portable device and checked up real-time action. The proposed algorithm may be helpful for various application for image enlargement and reconstruction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.281-289
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• 1998

Korea is developing a Korea Multi-Purpose Satellite I (KOMPSAT-1) as one of Korea National Space Program, which will be launched in 1999. The EOC (Electro-Optical Camera) is the primary payload for KOMP-SAT-1. The main mission of EOC is to provide the images for the production of scale maps of Korean territory. This research is focused on methodology and possibility for the production of topographic maps using EOC sensor. Since the imagery from EOC is not yet available, SPOT Level 1A image data which are quite similar to those of EOC, and Intergraph Imagestation (Digital Photogrammetric Workstation) are implemented in the process of sample digital map generation. The sample digital maps generated from SPOT stereoimages were compared and analyzed with the existing 1:50,000 scale digital map produced by National Geography Institute. The feasibility and problem encountered in 1:50,000 scale digital mapping using SPOT stereoimages were presented. Based on results, the feasibility and further research areas for KOMPSAT-EOC in the line of 1:25,000 and 1;50,000 digital mapping were discussed.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1925-1934
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• 2022

Monitoring nuclear activity for inaccessible areas using remote sensing technology is essential for nuclear non-proliferation. In recent years, deep learning has been actively used to detect nuclear-activity-related small objects. However, high-resolution satellite imagery containing small objects can result in class imbalance. As a result, there is a performance degradation problem in detecting small objects. Therefore, this study aims to improve detection accuracy by analyzing the effect of the ratio of small objects related to nuclear activity in the input data for the performance of the deep learning model. To this end, six case datasets with different ratios of small object pixels were generated and a U-Net model was trained for each case. Following that, each trained model was evaluated quantitatively and qualitatively using a test dataset containing various types of small object classes. The results of this study confirm that when the ratio of object pixels in the input image is adjusted, small objects related to nuclear activity can be detected efficiently. This study suggests that the performance of deep learning can be improved by adjusting the object pixel ratio of input data in the training dataset.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.18-26
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• 2009

Image resolution enhancement algorithm is a basic technique for image enlargement and restoration. The main problem is the image quality degradation such as blurring or blocking effects. In this paper, we propose loss information estimation and image resolution enhancement method using low level interpolation method. In the proposed method, loss information is computed by downsampling -interpolation process of obtained low resolution image. We estimate loss information of high resolution image using interpolation of the computed loss information. Lastly, we add up interpolated high resolution image and the estimated loss information which is applied a weight factor. Our experiments obtained the average PSNR 1.4dB which is improved results better than conventional algorithm. Also subjective image quality is more clearness and distinctness. The proposed method may be helpful for various video applications which required improvement of image.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.246-252
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• 2020

Safety accidents have been reported due to falling accumulated snow from cables of cable-supported bridges. In addition to the direct damage caused by falling snow, secondary damage, such as traffic accidents, can occur. Various methods have been proposed to prevent these accidents, but there are still problems in safety and practicality. In this study, a cable robot type was selected as one of the active methods for removing accumulated snow on cables. An attempt was made to increase the climbing ability of the robot to improve the efficiency of snow removal. In addition, the available range of cable diameter for the robot can be adjusted flexibly to be applied to cables used in the field. A high-resolution camera was also installed to check the surface condition of the cable in real time to increase the utility, and be used as a cable inspection robot. A three-axis accelerometer and a tension conversion algorithm were added to measure the tension force of cables. To verify the performance, indoor and field experiments were conducted, and future improvements for the inspection robot were proposed.

• The KIPS Transactions:PartC
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• v.17C no.2
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• pp.197-204
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• 2010

An effective integration of web-based learning environment and mobile device technology is considered as a new challenge to the developers. The screen size, however, of the mobile device is too small, and its performance is too inferior. Due to the foregoing limit of mobile technology, displaying bulk data on the mobile screen, such as a cyber lecture accompanied with real-time image transmission on the web, raises a lot of problems. Users have difficulty in recognizing learning contents exactly by means of a mobile device, and continuous transmission of video stream with bulky information to the mobile device arouses a lot of load for the mobile system. Thus, an application which is developed to be applied in PC is improper to be used for the mobile device as it is, a player which is fitting for the mobile device should be developed. Accordingly, this paper suggests mobile presentation using transcoding techniques of the field concerned. To display continuous video frames of learning image, such as a cyber lecture or remote lecture, by means of a mobile device, the performance difference between high-resolution digital image and mobile device should be surmounted. As the transcoding techniques to settle the performance difference causes damage of image quality, high-quality image may be guaranteed by application of trial and error between transcoding and selected learning resources.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.103-113
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• 2019

License plate recognition camera is dedicated device designed for acquiring images of the target vehicle for recognizing letters and numbers in a license plate. Mostly, it is used as a part of the system combined with server and image analysis module rather than as a single use. However, building a system for vehicle license plate recognition is costly because it is required to construct a facility with a server providing the management and analysis of the captured images and an image analysis module providing the extraction of numbers and characters and recognition of the vehicle's plate. In this study, we would like to develop an embedded type convergent camera (Edge Base) which can expand the function of the camera to not only the license plate recognition but also the security CCTV function together and to perform two functions within the camera. This embedded type convergence camera equipped with a high resolution 4K IP camera for clear image acquisition and fast data transmission extracted license plate area by applying YOLO, a deep learning software for multi object recognition based on open source neural network algorithm and detected number and characters of the plate and verified the detection accuracy and recognition accuracy and confirmed that this camera can perform CCTV security function and vehicle number plate recognition function successfully.

• Korean Journal of Optics and Photonics
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• v.34 no.4
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• pp.139-150
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• 2023

Despite various light detection and ranging (LiDAR) architectures, it is very difficult to achieve long-range detection and high resolution in both vertical and horizontal directions with a wide field of view (FOV). The scanning architecture is advantageous for high-performance LiDAR that can attain long-range detection and high resolution for vertical and horizontal directions. However, a large-area photodetector (PD), which is disadvantageous for detection speed, is essentially required to secure the wide FOV. Thus we propose a PD based on the static unitary detector (STUD) technique that can operate multiple small-area PDs as a single large-area PD at a high speed. The InP/InGaAs STUD PIN-PD proposed in this paper is fabricated in various types, ranging from 1,256 ㎛×949 ㎛ using 32 small-area PDs of 1,256 ㎛×19 ㎛. In addition, we measure and analyze the noise and signal characteristics of the LiDAR receiving board, as well as the performance and sensitivity of various types of STUD PDs. Finally, the LiDAR receiving board utilizing the STUD PD is applied to a 3D scanning LiDAR prototype that uses a 1.5-㎛ master oscillator power amplifier laser. This LiDAR precisely detects long-range objects over 50 m away, and acquires high-resolution 3D images of 320 pixels×240 pixels with a diagonal FOV of 32.6 degrees simultaneously.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.68-74
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• 2017

This paper presents a joint demosaicking and arbitrary-ratio down sampling algorithm for color filter array (CFA) images. Color demosaiking is a necessary part of image signal processing pipeline for many types of digital image recording system using single sensor. Also, such as smart phone, obtained high resolution image from image sensor has to be down-sampled to be displayed on the screen. The conventional solution is "Demosaicking first and down sampling later". However, this scheme requires a significant amount of memory and computational cost. Also, artifacts can be introduced or details get damaged during demosaicking and down sampling process. In this paper, we propose a method in which demosaicking and down sampling are working simultaneously. We use inverse mapping of Bayer CFA and then joint demosaicking and down sampling with arbitrary-ratio scheme based on signal decomposition of high and low frequency component in input data. Experimental results show that our proposed algorithm has better image quality performance and much less computational cost than those of conventional solution.