• Korean Journal of Optics and Photonics
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• v.17 no.4
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• pp.329-334
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• 2006

We have reconstructed 3-dimensional images by using the digital holographic microscope and the Mask-cut phase unwrapping algorithm. Off-axis holograms recorded with a magnified image of the microscopic object lens and reference beam are numerically reconstructed in amplitude and phase image by the Fresnel diffraction approximation. We have simultaneously reconstructed 2-dimensional and 3-dimensional images of the sub-micrometer objects.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.229-232
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• 2005

본 논문에서는 새로운 HAC(Histogram Area Calculation)방법과 영상의 객체분할 방법을 소개한다. 히스토그램을 이용한 영상은 색상 공간의 특징 때문에 조명에 매우 민감하여 빛의 강도에 따라 유사성이 저하되는 경우가 있다. 또한 공간적 정보를 가지고 있지 않아, 전혀 다른 모양의 영상일지라도 칼라 분포가 같은 영상으로 볼 수 있다. 이 논문에서 제안한 방법은 히스토그램 영역을 임의의 영역으로 나눠, 영역들의 유사성을 매칭(matching) 시킨다. 2차 검색방법으로 원 영상에서의 색상 질감 정보가 동일한 영역을 군집화 하여, 영상 분할된 객체들을 이용하여 검색하는 방법이다. 실험 결과, 제안한 방법이 전통적인 히스토그램 방법보다 검색 성능이 효율적인 결과를 얻었다.

• Korean Journal of Optics and Photonics
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• v.22 no.5
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• pp.214-218
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• 2011

In this paper we have applied self-reference hologram to DHM (digital holography microscopy) to remove phase aberration. We have constructed an off-axis reflection- type digital holography microscope. We have extracted a low spatial frequency hologram from the conjugated hologram and used it as a reference hologram. Experimentally we show that distortion of image and aberration of phase in a measurement system are removed using the self-reference hologram.

• Nuclear Engineering and Technology
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• v.53 no.6
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• pp.1947-1954
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• 2021

In the nuclear medicine imaging, quality control (QC) process using quadrant bar phantom is fundamental aspect of evaluating the spatial resolution. In addition, QC process of gamma camera is performed by daily or weekly. Recently, Monte Carlo simulation using the Geant4 application for tomographic emission (GATE) is widely applied in the pre-clinical nuclear medicine field for modeling gamma cameras with pixelated cadmium telluride (CdTe) semiconductor detector. In this study, we modeled a pixelated CdTe semiconductor detector and quadrant bar phantom (0.5, 1.0, 1.5, and 2.0 mm bar thicknesses) using the GATE tool. Similarity analysis based on correlation coefficients and peak signal-to-noise ratios was performed to compare image qualities for various source to collimator distances (0, 2, 4, 6, and 8 cm) and collimator lengths (0.2, 0.4, 0.6, 0.8, and 1.0 cm). To this end, we selected reference images based on collimator length and source to collimator distance settings. The results demonstrate that as the collimator length increases and the source to collimator distance decreases, the similarity to reference images improves. Therefore, our simulation results represent valuable information for the modeling of CdTe-based semiconductor gamma imaging systems and QC phantoms in the field of nuclear medicine.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.1-17
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• 2018

The living lab is a user-participatory innovation space where users can solve problems by themselves. Living Lab members are able to participate in all aspects of product development from technology conception. In this study, to prevent pedestrian accidents, auto-image sensing signal system was developed in Jeonju City, using the Living Lab method. In addition, we measured effectiveness of the auto-image sensing signal system with respect to pedestrian waiting time, pedestrian and driver signal violation, and pedestrian jaywalking. It was also compared the measures before installation, after installation and after applying Living Lab method. As a result, all of the three measures of effectiveness appeared to be more effective after Living Lab than after installation. Overall, this study is very significant in that it is the first case where the living lab is applied in transportation.

• Journal of Digital Convergence
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• v.12 no.5
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• pp.221-229
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• 2014

The study considers the meaning of the composite images created when users capture present images over past images tagged location data in using the mobile augmented reality technology. The composite image through the location-based augmented reality technology is the result of matching the same location data between present images users are capturing and past images captured already. It is the new composite images that contain two different narratives-current and past in the same space and in real-time. We developed the mobile application implemented augmented reality technology and analysed the process that users create multi-layered narrative in the middle of capturing present image through augmented reality module. In addition, through the comparison with similar studies and applications of the augmented reality, we found that the key to give the multi-narrative in the composite images is the user's participation to put its personal intentions in real-time capturing process. In further development, we'll be able to utilize the application in order that users easily create multi-layered narrative composite image using cultural and personal records.

• Journal of Digital Contents Society
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• v.19 no.2
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• pp.385-392
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• 2018

Iksan is one of medium city in Jellabukdo, South Korea. It has a favorable natural environment for the specialization potential of natural industries and development projects. In addition, it has various historical and cultural resources including Mireuksajji, and KTX Honam line which has been opened for a representative feature as transport city. However, it faces week connection with neighboring cities and large scale of development in neighboring areas, especially in Jeonju and Gunsan. In this paper, we try to classify the urban image assets of Iksan as 'Iksan Station' and 'ktx' on keywords and analyze the possibility of being a center of transportation and logistics through big data analysis extracted from SNS and website. In comparison with Gwangju Songjeong, KTX Honam line station, which has been developed with similar regional characteristics, it is aimed to establish the basis of improvement and establishment of urban image of Iksan city in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.1-12
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• 2012

The agricultural area was classified into dry and paddy fields in this study using the near-infrared band of Landsat TM to extract land cover classes that need to the application of Expected Mean Concentration (EMC) in nonpoint source works. The accuracy of image classification of the land cover map from Landsat TM image showed 83.61% and 78.41% respectively by comparing with the large and middle scale land cover map of Ministry of Environment. As the result of Soil Conservation Service (SCS) Curve Number (CN) using the land cover map from image classification, Dongbok dam and Dongbok stream basin were analyzed high. Also Geymbaek water-gage and Bosunggang upstream basin showed high in the analysis of EMC of BOD, TN, TP by basin. And also Geymbaek water-gage and Bosunggang upstream basin showed high in the analysis of non-point source through coupling with direct runoff. Therefore these basins were selected with the main area for the management of nonpoint source.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.107-108
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• 2008

본 논문에서는 8-bits의 그레이레벨 영상에서 그레이레벨(gray-level) 값들의 발생 빈도(frequency)에 따른 순위 변환(Ranking-Transformation)을 이용한 효율적인 무손실 압축을 제안한다. 제안한 기법은 서로 인접한 픽셀의 그레이레벨의 쌍에 대한 발생 빈도를 토대로 원 영상의 그레이레벨 값을 이에 대응하는 순위 값으로 변환시킨다. 이때 부가정보가 발생하지 않도록 입력영상의 픽셀들에 대하여 한 픽셀씩 순차적으로 지정한 순위로 재구성한다. 실험결과, 부가 정보 없이 입력 영상을 압축하게 되어 엔트로피 부호화기를 통한 디지털 영상들의 효율적인 압축 성능 향상을 기대할 수 있다.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1001-1007
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• 2020

In recent years, machine learning algorithms are continuously being used and expanded in various fields, such as facial recognition, signal processing, personal authentication, and stock prediction. In particular, various algorithms, such as deep learning, reinforcement learning, and Q-learning, are continuously being improved. Among these algorithms, the expansion of deep learning is rapidly changing. Nevertheless, machine learning algorithms have not yet been applied in several fields, such as personal authentication technology. This technology is an essential tool in the digital information era, walking recognition technology as promising biometrics, and technology for solving state-space problems. Therefore, algorithm technologies of deep learning, reinforcement learning, and Q-learning, which are typical machine learning algorithms in various fields, such as agricultural technology, personal authentication, wireless network, game, biometric recognition, and image recognition, are being improved and expanded in this paper.