• Journal of Digital Contents Society
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• v.19 no.1
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• pp.165-171
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• 2018

Shadow is a physical phenomenon observed in natural scenes and has a negative effect on various image processing systems such as intelligent video surveillance, traffic surveillance and aerial imagery analysis. Therefore, shadow detection should be considered as a preprocessing process in all areas of computer vision. In this paper, we define and analyze various feature elements for shadow detection in a single natural image that does not require a reference image. The shadow elements describe the intensity, chromaticity, illuminant-invariant, color invariance, and entropy image, which indicate the uncertainty of the information. The results show that the chromaticity and illuminant-invariant images are effective for shadow detection. In the future, we will define a fusion map of various shadow feature elements, and continue to study shadow detection that can adapt to various lighting levels, and shadow removal using chromaticity and illuminance invariant images.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.408-414
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• 2019

We developed a surveillance tool for collision avoidance of unmanned aerial vehicles (UAVs) in urban areas. In our tool, users can visualize the safety distance on the actual 3D map of urban area. The estimated positions of UAVs are assumed to be obtained based on the long-term evolution (LTE) signals. The safety distance is defined to include two or more signals with bias. The safety distance calculation method used in this paper enables simulation similar to the actual urban areas where signals are frequently biased due to multipath. In the simulation, the parameters were set based on the measured values, and the change of the safety distance according to the number of faulty signals was simulated. As a result, increasing the number of faulty signals led to a longer safety distance as expected.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.807-817
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• 2019

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden-Fletcher-Goldfarb-Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and nondiagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.3
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• pp.326-329
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• 2016

UAVs(Unmanned Aerial Vehicle) can be used in variant fields fornot only combat, but also recon, observation and exploration. Moreover, UAVs capacity can be expanded to impossible missions for existing surveillance system such as SAR(Synthetic Aperture Radar) technology that collecting images from all weather conditions. In recent days, with development of highly efficient IC and lightened system technology, there are significant increase of researches and demands to make SAR sensor as a payload of UAV. Therefore, this paper contains development process and results of small signal generator and RF device as a core module of SAR system based on the digital device of DDS.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.4
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• pp.33-39
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• 2006

In this paper, the collision avoidance of Unmanned Aerial Vehicles(UAVs) by applying the Traffic alert and Collision Avoidance System II(TCAS-II) is introduced. The performances of two UAVs whose maximum vertical rates are different each other are compared and analysed by not only converting many TCAS-II commands into an autopilot input but also implementing a computer program based on the Minimum Operational Performance Standards for TCAS-II. As the alternative to a possible Near Mid-Air Collision for UAVs whose maximum vertical rates are low, we have proposed a modified algorithm considering the maximum vertical rate and altitude. The modified algorithm is available on the assumption that a wider surveillance range is provided by a ADS-B system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.6
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• pp.488-496
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• 2015

This paper proposes a framework to determine the routes of multiple unmanned aerial vehicles (UAVs) to conduct multiple tasks in different locations considering the survivability of the vehicles. The routing problem can be formulated as the vehicle routing problem (VRP) with different cost matrices representing the trade-off between the safety of the UAVs and the mission completion time. The threat level for a UAV at a certain location was modeled considering the detection probability and the shoot-down probability. The minimal-cost path connecting two locations considering the threat level and the flight distance was obtained using the Dijkstra algorithm in hexagonal cells. A case study for determining the optimal routes for a persistent multi-UAVs surveillance and reconnaissance missions given multiple enemy bases was conducted and its results were discussed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.3
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• pp.267-274
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• 2009

Recently, UAVs (Unmanned Aerial Vehicles) are expected much as the Unmanned Systems for various missions. These missions are often based on the Vision System. Especially, missions such as surveillance and pursuit have a process which is carried on through the transmitted vision data from the UAV. In case of small UAVs, monocular vision is often used to consider weights and expenses. Research of missions performance using the monocular vision is continued but, actually, ground and target model have difference in distance from the UAV. So, 3D distance measurement is still incorrect. In this study, Mean-Shift Algorithm, Optical Flow and Subspace Method are posed to estimate the relative depth. Mean-Shift Algorithm is used for target tracking and determining Region of Interest (ROI). Optical Flow includes image motion information using pixel intensity. After that, Subspace Method computes the translation and rotation of image and estimates the relative depth. Finally, we present the results of this study using images obtained from the UAV experiments.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.212-225
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• 2015

UAV (Unmanned Aerial Vehicle), the pilotless plane or drone, draws researchers' attention at these days for its extended use to various area. The research was initiated for military use of the UAV, but the area of applicable field is extended to surveillance, communication, and even delivery for commercial use. As increasing the interest in UAV, the needs of research for operating the flying object which is not directly visible when it conducts a certain mission to remote place is obviously grown as much as developing high performance pilotless plane is required. One of the project supported by government is related to the use of UAV for logistics fields and controlling UAV to deliver the certain items to isolated or not-easy-to-access place is one of the important issues. At the initial stage of the project, the previous researches for controlling UAV need to be organized to understand current state of art in local researches. Thus, this study is one of the steps to develop the unmanned system for using in military or commercial. Specifically, we focused on reviewing the approaches of controlling UAV from origination to destination in previous in-country researches because the delivery involves the routing planning and the efficient and effective routing plan is critical to success to delivery mission using UAV. This routing plan includes the method to avoid the obstacles and reach the final destination without a crash. This research also present the classification and categorization of the papers and it could guide the researchers, who conduct researches and explore in comparable fields, to catch the current address of the research.

• Journal of the Korean GEO-environmental Society
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• v.19 no.12
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• pp.65-72
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• 2018

The uses of unmanned aerial vehicles (UAV) have been expanding in agriculture surveys, obtaining real time updates of dangerous facilities where human access is difficult, disaster monitoring, and 3D modeling. In reality, there is an upsurge in the application of UAVs in fields like, construction, infrastructure, imaging, surveying, surveillance and transportation. Especially, when the slope failure such as landslide occurs, the uses of UAVs are increasing. Since, the UAVs can fly in three dimensions, they are able to obtain spatial data in places where human access is nearly impossible. Despite of these advantages, however, the uses of UAVs are still limited during slope failure. In order to overcome these limitations, this study computes the soil volume change during slope failure through the computation technique using photogrammetric information obtained from UAV system. Through this study, it was found that photogrammetric information from UAV can be used to acquire information on amount of earthworks required for repair works when slope collapse occurs in mountainous areas, where human access in difficult.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.239-242
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• 2016

In recent years, Unmanned Aerial Vehicles (UAV) have been developed for both military and civilian activities in regions where the presence of onboard human pilots is risky or not necessary. However, UAV require a high demand of power to achieve its missions such as taking images/videos in a certain area or surveillance activities. Therefore, this situation triggers the need of techniques to reduce power consumption for UAV to complete its mission safely. One of the methods is to use a waypoint optimization procedure which deals with a pre-specified set of waypoints to find a minimum route to fly through those waypoints in order to reduce power consumption. In this paper, due to the UAV's multidisciplinary which makes it impossible to be represented as an analytical model, we design a simulation model of UAV using MATLAB Simulink and AeroSim Blockset, an analysis package in aerospace industry. The simulation model is then coupled with optimization algorithms along with a set of waypoints (flight path) in order to measure at which percentage power consumption can be minimized for UAV.