• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.85-94
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• 2023

Image halftoning is a technique for varying grayscale images into two-tone binary images. Unfortunately, the static representation of an image-half toning, wherever each pixel intensity is combined by its local neighbors only, causes missing subjective problem. Also, the existing noise causes an instability criterion. In this paper an image half-toning is represented as a dynamical system for recognizing the global representation. Also, noise is reduced based on a probabilistic model. Since image half-toning is considered as 2-D matrix with a full connected pass, this structure is recognized by the dynamical system of Cellular Neural Networks (CNNs) which is defined by its template. Bayesian Rough Sets is used in exploiting the ideal CNNs construction that synthesis its dynamic. Also, Bayesian rough sets contribute to enhance the quality of the halftone image by removing noise and discovering the effective parameters in the CNNs template. The novelty of this method lies in finding a probabilistic based technique to discover the term of CNNs template and define new learning rules for CNNs internal work. A numerical experiment is conducted on image half-toning corrupted by Gaussian noise.

• Spatial Information Research
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• 제13권3호
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• pp.211-220
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• 2005

건설교통부에서는 기존의 도로현황을 더욱 빠르고 정확하게 파악하기 위해 도로관리통합시스템에서 전국의 일반국도에 대해 위치정보를 가진 디지털 영상을 제공하는 방안을 추진 중에 있다. 이를 위해 한국건설기술연구원에서는 도로를 주행하면서 일정거리간격으로 2매의 고해상도의 칼라 CCD영상을 취득할 수 있는 도로영상취득차량을 개발하였다. 본 논문에서는 특히 영상취득 S/W와 동기화장치 개발에 대해 기술하였으며 실험을 통해 차량의 궤적 정확도, 영상취득 S/W, 동기화 장치의 성능을 검토한 결과 도로관리통합시스템에서 필요한 도로영상을 취득하는데 적합한 것으로 판단된다.

• 한국측량학회지
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• 제36권3호
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• pp.197-202
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• 2018

Drone has been continuously studied in the field of geography and remote sensing. The basic researches have been actively carried out before the utilization in the field of photogrammetry. In Korea, it is necessary to study the actual way of research in accordance with the drone utilization environment. In particular, analysis on the characteristics of DSM (Digital Surface Model) generated through drone are needed. In this study, the characteristic of drone DSM as a data acquisition method was analyzed for coastal management. The coastal area was selected as the study area, and data was acquired by using drone. As a result of the study, the terrain model and the ortho image of coastal area were produced. The accuracy of UAV (Unmanned Aerial Vehicle) results were very high about 10cm at check points. However, concavo-convex shapes appeared in very flat areas such as tidal flats and roads. To correct this terrain model distortion, a new terrain model was created through data processing and the results were evaluated. If additional studies are carried out and the construction and analysis of terrain model using drone image is done, drone data for coastal management will be available.

• 한국지반신소재학회논문집
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• 제21권1호
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• pp.33-48
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• 2022

This paper presents illustrative examples of the application of advanced digital image correlation (DIC) technology in the geotechnical laboratory tests, such as shallow footing test, trapdoor test, retaining wall test, and wide width tensile test on geogrid. The theoretical background of the DIC technique is first introduced together with fundamental equations. Relevant reduced-scale model tests were then performed using standard sand while applying the DIC technique to capture the movement of target materials during tests. A number of different approaches were tried to obtain optimized images that allow efficient tracking of material speckles based on the DIC technique. In order to increase the trackability of soil particles, a mix of dyed and regular sand was used during the model tests while specially devised painted speckles were applied to the geogrid. A series of images taken during tests were automatically processed and analyzed using software named VIC-2D that automatically generates displacements and strains. The soil deformation field and associated failure patterns obtained from the DIC technique for each test were found to compare fairly well with the theoretical ones. Also shown is that the DIC technique can also general strains appropriate to the wide width tensile test on geogrid, It is demonstrated in this study that the advanced DIC technique can be effectively used in monitoring the deformation and strain field during a reduced-scale geotechnical model laboratory test.

• 드라이브 ㆍ 컨트롤
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• 제18권4호
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• pp.9-18
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• 2021

This study proposes a method for creating learning datasets to recognize obstacles using deep learning algorithms in automated construction machinery or an autonomous vehicle. Recently, many researchers and engineers have developed various recognition algorithms based on deep learning following an increase in computing power. In particular, the image classification technology and image segmentation technology represent deep learning recognition algorithms. They are used to identify obstacles that interfere with the driving situation of an autonomous vehicle. Therefore, various organizations and companies have started distributing open datasets, but there is a remote possibility that they will perfectly match the user's desired environment. In this study, we created an interface of the virtual simulator such that users can easily create their desired training dataset. In addition, the customized dataset was further advanced by using the RDBMS system, and the recognition rate was improved.

• 한국공간구조학회논문집
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• 제22권2호
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• pp.19-27
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• 2022

Visual inspection methods have limitations, such as reflecting the subjective opinions of workers. Moreover, additional equipment is required when inspecting the high-rise buildings because the height is limited during the inspection. Various methods have been studied to detect concrete cracks due to the disadvantage of existing visual inspection. In this study, a crack detection technology was proposed, and the technology was objectively and accurately through AI. In this study, an efficient method was proposed that automatically detects concrete cracks by using a Convolutional Neural Network(CNN) with the Orthomosaic image, modeled with the help of UAV. The concrete cracks were predicted by three different CNN models: AlexNet, ResNet50, and ResNeXt. The models were verified by accuracy, recall, and F1 Score. The ResNeXt model had the high performance among the three models. Also, this study confirmed the reliability of the model designed by applying it to the experiment.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2007년도 춘계학술발표회 논문집
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• pp.107-110
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• 2007

There it has been progressed study about the city of land use and change detection in different period. The aim of the study is to find the differences in spatial change for subway construction lines using Landsat TM and SPOT image. The result of study to use judge the data in subway role about the city growth. In the recently, it will be expected to use important basis data in development of the city.

• 한국CDE학회논문집
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• 제9권2호
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• pp.148-157
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• 2004

Interactive simulators that simulate mechanical systems are being developed for the purpose of performance evaluation of product design, replacement of physical training, and entertainment game. Use of flight simulator is increasing to reduce risk and cost of physical training, and we need virtual environment which covers large area terrain. We need a method that can reduce development cost and construction time of virtual environment that simulate the real environment. There have been attempts to link GIS or remote sensing field with virtual reality. This paper examines a method that helps to construct virtual environment, and attempts to link geographic information with virtual reality. A construction method of virtual environment based on digital map and satellite image has been studied.

• 환경영향평가
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• 제23권2호
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• pp.150-156
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• 2014

The aim of this study is to detection of changed vegetation area of Saemangeum tidal flat with comparison of topography and surface sediments during the dyke construction. Sedimentary facies of four seasons of 2001 from inside Saemangeum tidal flat revealed homogeneous layers in the upper part, however near sea side tidal flat were detecting with carried out rapid sediment deposition during the dyke construction using satellite image spatial analysis. The sedimentation types inside Saemangeum tidal flat were classified with vegetation types, which were well matched with the sedimentation pattern revealed by change in vegetation patterns.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.563-566
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• 2006

In order for the evaluation and analysis of the spring drought which has been periodically occurring in Korean peninsula since 2000, the use of satellite image data is increasing to investigate temporal and spatial characteristics of the drought areas. The recent spring droughts in south Korea have some characteristics. It last for short period in spring when the activity of vegetation is not lively and it have large areal deviation in the severity of drought. In this study, considering the characteristics of the spring drought in Korean peninsular, the MODIS satellite image data which has superior spatial and radiometric resolutions was used for the analysis of the spring drought. In two basins having different spatial characteristics, the drought events were selected and their severities were analyzed using the MODIS NDVI, LSWI, and daily rainfall data since 2000, and the spatial characteristics of the drought area were analyzed using the DEM, land cover, and digital forest map of the study areas.