• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.628-629
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• 2018

Recently, residential spaces in urban areas have changed into multi - family residential spaces. There is a feature that smoke is charged when a fire occurs here. Also, the evacuation route and the direction of the outflow of smoke are the same, and the possibility of inhaling the smoke of the evacuees is very high. When fighting fire in a narrow residential space such as a dwelling in a downtown area, exploration is the most important. For this purpose, we implement EO / IR sensor which can be mounted on firefighter 's helmet and can be used for fire detection. By using the EO / IR operation test, we can derive the results that can be used for research and development of the fire search sensor.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.522-529
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• 2018

FOD refers to various metals and non-metallic foreign substances that pose a risk to aircraft. FODs occur in all areas and time zones, including runways, taxiways, and maintenance facilities, and pose a fatal hazard to aircraft safety during aircraft movements and take-off and landing. Rapid and effective detection and removal of FODs in the runway is required. As part of recent developments in aviation safety technologies, automatic detection of debris in runways in airports is under way. In this paper, we conducted an automated detection test using the EO/IR camera and radar at the Taean campus of Hansu University to confirm normal detection during the day and night.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.1
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• pp.39-45
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• 2022

In this paper, we propose methods to improve image-based auto-focus that can compensate for drawbacks of traditional auto-focus control. When adjusting the focus, there is a problem that the focus window cannot be set to the same position if the camera's LOS is not directed at the same location and flow or shake. To address this issue, we applied image tracking techniques to improve optimal focus localization accuracy. And also, although the same focus value should be calculated at the same focus step, but different values can be calculated by camera's fine shaking or image disturbance due to atmospheric scattering. To tackle this problem a SAFS (Stable Adjacency Frame Selection) has been proposed. As a result of this study, our proposed methodology shows more accurate than traditional methods in terms of finding best focus position.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.743-748
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• 2008

This paper presents an inertia type of piezostack based active mount for unmanned aero vehicle (UAV) camera system. After identifying the stiffness and damping properties of the rubber element and piezostack a mechanical model of the active mount system is established. The governing equation of mount is them derived and expressed in a state space farm. Subsequently, a sliding mode controller which is robust to uncertain parameters is designed in order to reduce the vibration imposed according to the military specification associated with UAV camera mount system operation. Control performances such as acceleration and transmitted force are evaluated through both computer simulation and experimental implementation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.12
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• pp.1278-1285
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• 2008

This paper presents an inertia type of piezostack based active mount fur unmanned aero vehicle (UAV) camera system. After identifying the stiffness and damping properties of the rubber element and piezostack a mechanical model of the active mount system is established. The governing equation of mount is then derived and expressed in a state space form. Subsequently, a sliding mode controller which is robust to uncertain parameters is designed in order to reduce the vibration imposed according to the military specification associated with UAV camera mount system operation. Control performances such as acceleration and transmitted force are evaluated through both computer simulation and experimental implementation.

• Electronics and Telecommunications Trends
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• v.37 no.1
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• pp.10-20
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• 2022

A drone without attaching guns or bombs can be a dangerous weapon, since its motor speed is greater than 3000 rpm, which is similar to that of a mower powered by a LiPo battery. The anti-drone system is the only means of detecting and neutralizing drone attacks. Many defense companies around the world provide solutions using various types of equipment (for example, radar, cameras, jamming guns, and net guns). ETRI has also developed a Low-Altitude Drone Detection (LADD) system consisting of Ku-band radar and an Electro-Optical/Infra-Red (EO/IR) camera. In this paper, we summarize recent technical advances in anti-drone systems around the world and introduce the features and describe the performance of the LADD system.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.5
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• pp.545-553
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• 2012

A Gimbal structure system in observation reconnaissance aircraft is made up of camera module and stabilization drive device supporting camera module. During flight for image recording, the aircraft undergoes serious accelerations with wide frequencies due to several factors. Though base excitation of stabilization drive device induces vibration of camera module, it must get the stable and clean images. To achieve this aim, acceleration of camera module must be reduced. Hence, vibration isolators were installed to stabilization drive device. Considering isolators and bearings in the stabilization drive device, vibration characteristics of gimbal structure system were analyzed by finite element method. For three translational direction, acceleration transmissibility of camera module was calculated by harmonic responses analysis in the frequency range of 5 ~ 500 Hz. In addition to, sine-sweep experiment were performed to prove correctness of present analysis.

• Journal of Advanced Navigation Technology
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• v.23 no.6
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• pp.495-500
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• 2019

Foreign object debris (FOD) is a generic term for various metals and non-metal foreign object and materials with potential hazards to aircraft operations. Since the method of manual FOD detection and collection in the aircraft moving area is very low in efficiency and economic efficiency, it is essential to develop to FOD automatic detection system suitable for domestic environment. This paper is the result of the performance comparison test results of the two systems for the combined operation of each optimal detection time and 95% accuracy above 100 m for complex operation using the fixed FOD automatic detection system and the mobile FOD system using EO/IR camera and radar at Taean Airfield Hanseo University. It is expected that FOD can be performed unattended through continuous R & D.

• Korean Journal of Optics and Photonics
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• v.25 no.5
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• pp.245-253
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• 2014

We report a realistic field-performance simulation for a new MWIR camera. It is designed for early detection of missile plumes over a distance range of a few hundred kilometers. Both imaging and radiometric performance of the camera are studied by using real-scale integrated ray tracing, including targets, atmosphere, and background scene models. The simulation results demonstrate that the camera would satisfy the imaging and radiometric performance requirements for field operation.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.3-12
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• 2022

Image deblurring aims to remove image blur, which can be generated while shooting the pictures by the movement of objects, camera shake, blurring of focus, and so forth. With the rise in popularity of smartphones, it is common to carry portable digital cameras daily, so image deblurring techniques have become more significant recently. Originally, image deblurring techniques have been studied using traditional optimization techniques. Then with the recent attention on deep learning, deblurring methods based on convolutional neural networks have been actively proposed. However, most of them have been developed while focusing on better performance. Therefore, it is not easy to use in real situations due to the speed of their algorithms. To tackle this problem, we propose a novel deep learning-based deblurring algorithm that can be operated in real-time on HD resolution. In addition, we improved the training and inference process and could increase the performance of our model without any significant effect on the speed and the speed without any significant effect on the performance. As a result, our algorithm achieves real-time performance by processing 33.74 frames per second at 1280×720 resolution. Furthermore, it shows excellent performance compared to its speed with a PSNR of 29.78 and SSIM of 0.9287 with the GoPro dataset.