• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.55-64
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• 2013

In this paper, the HILS (Hardware In-the-Loop Simulation) system to analyze and to verify the performance of the targeting pod is addressed. The main functions of the targeting pod is acquiring and tracking targets to guide a LGB (Laser Guided Bomb) to the targets. For the analysis of targeting pod, the real time simulate images generation of IR and daylight cameras, sever control technology, and the analysis of laser transfer characteristics are necessary. For the real time image generation and the laser transfer characteristics analysis, off-the-shelf SDK(Software Development Kit) OKTAL-SE is used. For the servo controller, well-proven mechanism in the previous program is applied to increase servo control accuracy. To analyze the performance of a targeting pod in a realistic environment, 1553B, ARINK818 interface and etc. which are actually implemented in real combat aircrafts are applied in the system. By using the developed HILS system, the performance of currently operating targeting pods in real combat aircrafts can be analyzed and predicted. Additionally, the relationship between overall system performance and each module performance can be analyzed, the currently developed HILS system is expected to be a very useful tool to generate system development requirements of targeting pods and to reduce any possible future development risks.

• Journal of the Korean Society for Computer Game
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• v.31 no.4
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• pp.61-70
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• 2018

In this paper, we propose a synchronized playback method of 3D reference model and video by extracting golf swing information from learner's golf video to precisely compare and analyze each motion in each position and time in the golf swing, and present the implementation result. In order to synchronize the 3D model with the learner's swing video, the learner's golf swing movie is first photographed and relative time information is extracted from the photographed video according to the position of the golf club from the address posture to the finishing posture. Through applying time information from learners' swing video to a 3D reference model that rigs the motion information of a pro-golfer's captured swing motion at 120 frames per second through high-quality motion capture equipment into a 3D model and by synchronizing the 3D reference model with the learner's swing video, the learner can correct or learn his / her posture by precisely comparing his or her posture with the reference model at each position of the golf swing. Synchronized playback can be used to improve the functionality of manually adjusting system for comparing and analyzing the reference model and learner's golf swing. Except for the part where the image processing technology that detects each position of the golf posture is applied, It is expected that the method of automatically extracting the time information of each location from the video and of synchronized playback can be extended to general life sports field.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1669-1683
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• 2021

AI intelligent agriculture and digital agriculture are important for the science of agriculture. Leaf chlorophyll contents(LCC) are one of the most important indicators to determine the growth status of vegetable crops. In this study, a support vector machine (SVM) regression model was produced using an unmanned aerial vehicle-based RGB camera and a multispectral (MSP) sensor for onions and garlic, and the LCC estimation applicability of the RGB camera was reviewed by comparing it with the MSP sensor. As a result of this study, the RGB-based LCC model showed lower results than the MSP-based LCC model with an average R² of 0.09, RMSE 18.66, and nRMSE 3.46%. However, the difference in accuracy between the two sensors was not large, and the accuracy did not drop significantly when compared with previous studies using various sensors and algorithms. In addition, the RGB-based LCC model reflects the field LCC trend well when compared with the actual measured value, but it tends to be underestimated at high chlorophyll concentrations. It was possible to confirm the applicability of the LCC estimation with RGB considering the economic feasibility and versatility of the RGB camera. The results obtained from this study are expected to be usefully utilized in digital agriculture as AI intelligent agriculture technology that applies artificial intelligence and big data convergence technology.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.833-845
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• 2021

Quantification of carbon absorption and understanding the human induced land use changes forms one of the major study with respect to global climatic changes. An attempt study has been made to quantify the carbon absorption by land use changes through remote sensing technology. However, it focused on past carbon absorption changes. So prediction of future carbon absorption changes is insufficient. This study simulated land use change using the Conversion of Land Use and its Effects at Small regional extent (CLUE-S) model and predicted future changes in carbon absorption considering climate change scenarios 4.5 and 8.5 of the Representative Concentration Pathways (RCP). Results of this study, in the RCP 4.5 scenarios there predicted to be loss of 7.92% of carbon absorption, but in the RCP 8.5 scenarios was 13.02%. Therefore, the approach used in this study is expected to enable exploration of future carbon absorption change considering other climate change scenarios.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.34-41
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• 2021

Sidewalks are facilities used for the safe and comfortable passage of pedestrians and are paved with blocks of various materials. Currently, Korea does not have a quantitative survey method for the pavement condition of sidewalks, so it is necessary to develop an efficient survey method. Drones are being used as an efficient survey tool in various fields, but there are limited studies in which sidewalks have been investigated. This study investigates the possibility of detection by limiting the missing sidewalk blocks using a drone. This study is an initial study on the development of a method for detecting damage in sidewalk blocks. For this, sidewalk blocks were artificially removed to simulate a dropout situation, and images were acquired with 0.7-cm resolution using a drone. As a characteristic of the point cloud data acquired through image pre-processing, there was high variance of the elevation of the points in the missing area of the sidewalk block. Using these characteristics, an experiment was conducted to detect the missing parts of the sidewalk block by applying four thresholds to the variance of the elevation of points included in the grid corresponding to the sidewalk area. As a result, the detection accuracy was shown with a positive detection ratio of 70-80%, omission errors of 20-30%, and commission errors lower than 2%. It is judged that the possibility of detecting missing sidewalk blocks is high. This study focused on detecting a simulated missing sidewalk block in a limited environment. Therefore, it is expected that an efficient and quantitative method of detecting damaged sidewalk blocks can be developed in the future through additional research with considerations of the actual environment.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1975-1984
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• 2021

Urban expansion results in raising the temperature in the city, which can cause social, economic and physical damage. In order to prevent the urban heat island and reduce the urban land surface temperature, it is important to quantify the cooling effect of the features of the urban space. Therefore, in order to understand the relationship between each object of land cover and the land surface temperature in Seoul, the land cover map was classified into 6 classes. And the correlation and multiple regression analysis between land surface temperature and the area of objects, perimeter/area, and normalized difference vegetation index was analyzed. As a result of the analysis, the normalized difference vegetation index showed a high correlation with the land surface temperature. Also, in multiple regression analysis, the normalized difference vegetation index exerted a higher influence on the land surface temperature prediction than other coefficients. However, the explanatory power of the derived models as a result of multiple regression analysis was low. In the future, if continuous monitoring is performed using high-resolution MIR Image from KOMPSAT-3A, it will be possible to improve the explanatory power of the model. By utilizing the relationship between such various land cover types considering vegetation vitality of green areas with that of land surface temperature within urban spaces for urban planning, it is expected to contribute in reducing the land surface temperature in urban spaces.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.95-111
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• 2021

As the population decreases in an aging society, the average age of drivers increases. Accordingly, the elderly at high risk of being in an accident need autonomous-driving vehicles. In order to secure driving safety on the road, several technologies to respond to various obstacles are required in those vehicles. Among them, technology is required to recognize static obstacles, such as poor road conditions, as well as dynamic obstacles, such as vehicles, bicycles, and people, that may be encountered while driving. In this study, we propose a deep neural network algorithm capable of simultaneously detecting these two types of obstacle. For this algorithm, we used 1,418 road images and produced annotation data that marks seven categories of dynamic obstacles and labels images to indicate road damage. As a result of training, dynamic obstacles were detected with an average accuracy of 46.22%, and road surface damage was detected with a mean intersection over union of 74.71%. In addition, the average elapsed time required to process a single image is 89ms, and this algorithm is suitable for personal mobility vehicles that are slower than ordinary vehicles. In the future, it is expected that driving safety with personal mobility vehicles will be improved by utilizing technology that detects road obstacles.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.62-77
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• 2019

Open Data Cube(ODC) has been emerging and developing as the open source platform in the Committee on Earth Observation Satellites(CEOS) for the Global Earth Observation System of Systems(GEOSS) deployed by the Group on Earth Observations (GEO), ODC can be applied to the deployment of scalable and large amounts of free and open satellite images in a cloud computing environment, and ODC-based country or regional application services have been provided for public users on the high performance. This study first summarizes the status of ODC, and then presents concepts and some considering points for linking this platform with Korea Multi-Purpose Satellite (KOMPSAT) images. For the reference, the main contents of ODC with the Google Earth Engine(GEE) were compared. Application procedures of KOMPSAT satellite image to implement ODC service were explained, and an intermediate process related to data ingestion using actual data was demonstrated. As well, it suggested some practical schemes to utilize KOMPSAT satellite images for the ODC application service from the perspective of open data licensing. Policy and technical products for KOMPSAT images to ODC are expected to provide important references for GEOSS in GEO to apply new satellite images of other countries and organizations in the future.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.3
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• pp.71-80
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• 2019

The Fourth Industrial Revolution, centered on intelligence and information, began to take hold in 2016. This study uses virtual reality technology, which is the most popular technology of the Fourth Industrial Revolution. The purpose of this study is to explore a Virtual Walk-through method, which can be easily applied to landscape architecture. At present, virtual reality technology is widely used in the fields of games, emergency training, and architectural design. However, in the field of landscape architecture, it is still in the development stage. In addition, most of the traditional ways to display virtual reality use 2D images, but such methods have some limitations. Therefore, this research addresses the three stages of "design-exhibition-experience" and puts forward a new simple method called 'Virtual Walk-through' that breaks from traditional landscape design exhibitions. The results show that compared with traditional methods, virtual reality has many advantages, such as the freedom of experience, a diversity of viewing angles, information supply, interaction, etc. It can show high quality images and effects, which are suitable for landscape design. It provides an evaluation method for garden design that can be utilized in the future. It is simple and has value as it can reflect the method and the expected effects. Virtual reality technology can bring an infinite number of prospects to the development of landscape architecture.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.3
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• pp.191-197
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• 2019

As the shipbuilding and offshore plant industries grow larger and more complex, their maintenance and inspection systems become more important. Recently, maintenance and inspection systems based on augmented reality have been attracting much attention for improving worker's understanding of work and efficiency, but it is often difficult to work with because accurate matching between the augmented model and reality information is not. To solve this problem, marker based AR technology is used to attach a specific image to the model. However, the markers get damaged due to the characteristic of the shipbuilding and offshore plant industry, and the camera needs to be able to detect the entire marker clearly, and thus requires sufficient space to exist between the operator. In order to overcome the limitations of the existing AR system, in this study, a markerless AR was adopted to accurately recognize the actual model of the pipe system that occupies the most processes in the shipbuilding and offshore plant industries. The matching methodology. Through this system, it is expected that the twist phenomenon of the augmented model according to the attitude of the real worker and the limited environment can be improved.