• 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 Aerospace System Engineering
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• v.17 no.2
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• pp.38-44
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• 2023

This study aims to determine how agricultural drones are operated for flight tests using a 5G communication in order to carry out a mission such as sensing agricultural crop healthy status with special cameras. Drones were installed with a multi-spectral and IR camera to capture images of crop status in separate altitudes with different speeds. A multi-spectral camera can capture crop image data using five different particular wavelengths with a built-in GPS so that captured images with synchronized time could provide better accuracy of position and altitude during the flight time. Captured thermal videos are then sent to a ground server to be analyzed via 5G communication. Thus, combining two cameras can result in better visualization of vegetation areas. The flight test verified how agricultural drones equipped with special cameras could collect image data in vegetation areas.

• Progress in Medical Physics
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• v.15 no.3
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• pp.156-160
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• 2004

An essential quality assurance (QA) procedure in high dose rate (HDR) remote after-loading brachytherapy is that of the verification of the Ir-192 HDR source positioning accuracy. A number of methods using mechanical rulers or autoradiograph and video cameras have been reported to check the positional error of the Ir-192 source. In this study, the feasibility of a CMOS (Complementary Metal Oxide Semiconductor) PC camera, with a fluorescent screen, was investigated. The agreement between the planned and measured dwell position was better than 1 mm and dwell times better than 0.4 sec. Our results indicate that the CMOS PC camera system could be used as a QA tool for the on-line determination of the source position and dwell time.

• The Research Journal of the Costume Culture
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• v.31 no.1
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• pp.107-123
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• 2023

This research studied the electrical characteristics, IR transmission characteristics, stealth functions, and thermal characteristics of infrared thermal-imaging cameras of copper-sputtered samples. Nylon samples were prepared for each density as a base material for copper-sputtering treatment. Copper-sputtered NFi, NM1, NM2, NM3, NM4, and NM5, showed electrical resistance of 0.8, 445.7, 80.7, 29.7, 0.3, and 2.2 Ω, respectively, all of which are very low values; for the mesh sample, the lower the density, the lower the electrical resistance. Measuring the IR transmittance showed that the infrared transmittance of the copper-sputtered samples was significantly reduced compared to the untreated sample. Compared to the untreated samples, the transmittance went from 92.0-64.1%. When copper sputtered surface was directed to the IR irradiator, the IR transmittance went from 73.5 to 43.8%. As the density of the sample increased, the transmittance tended to decreased. After the infrared thermal imaging, the absolute values of △R, △G, and △B of the copper phase increased from 2 to 167, 98 to 192, and 7 to 118, respectively, and the closer the density of the sample (NM5→NFi), the larger the absolute value. This proves that the dense copper phase-up sample has a stealth effect on the infrared thermal imaging camera. It is believed that the copper-sputtered nylon samples produced in this study have applications in multifunctional uniforms, bio-signal detection sensors, stage costumes, etc.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.493-505
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• 2023

Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.

• The Journal of the Korea Contents Association
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• v.10 no.8
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• pp.11-17
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• 2010

In this paper, we propose HMM-based upper-body gesture. First, to recognize gesture of space, division about pose that is composing gesture once should be put priority. In order to divide poses which using interface, we used two IR cameras established on front side and side. So we can divide and acquire in front side pose and side pose about one pose in each IR camera. We divided the acquired IR pose image using SVM's non-linear RBF kernel function. If we use RBF kernel, we can divide misclassification between non-linear classification poses. Like this, sequences of divided poses is recognized by gesture using HMM's state transition matrix. The recognized gesture can apply to existent application to do mapping to OS Value.

• Electronics and Telecommunications Trends
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• v.33 no.3
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• pp.78-88
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• 2018

As the unmanned aerial vehicle industry and its related technologies grow each year, the number of abuse cases caused by drones is increasing. In addition to the invasion of privacy caused by indiscriminate photography, terrorism using unmanned aerial vehicles, which have a low detection probability, high location accuracy, and the capability of targeting people or places, as well as carrying chemicals, radiation materials, and small bombs, is becoming a significant problem around the world. Accordingly, many companies are developing anti-drone solutions that consist of various technologies such as radar, EO/IR cameras, and RF jammers to detect and disable unmanned aerial vehicles. This article briefly introduces the recent R&D trends and technical levels of anti-drone technologies.

• International Journal of Contents
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• v.6 no.4
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• pp.49-56
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• 2010

In this paper we present a system that enables the user to interact with large display system even without touching the screen. With two infrared sensitive cameras mounted on the bottom left and bottom right of the display system pointing upwards, the user fingertip position on the selected region of interest of each camera view is found using vertical intensity profile of the background subtracted image. The position of the finger in two images of left and right camera is mapped to the display screen coordinate by using pre-determined matrices, which are calculated by interpolating samples of user finger position on the images taken by pointing finger over some known coordinate position of the display system. The screen is then manipulated according to the calculated position and depth of the fingertip with respect to the display system. Experimental results demonstrate an efficient, robust and stable human computer interaction.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.4
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• pp.293-298
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• 2006

In this paper, a sensor fusion based robot navigation method for the autonomous control of a miniature human interaction robot is presented. The method of navigation blends the optimality of the Fuzzy Neural Network(FNN) based control algorithm with the capabilities in expressing knowledge and learning of the networked Intelligent Robotic Space(IRS). States of robot and IR space, for examples, the distance between the mobile robot and obstacles and the velocity of mobile robot, are used as the inputs of fuzzy logic controller. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a sensor fusion technique is introduced, where the sensory data of ultrasonic sensors and a vision sensor are fused into the identification process. Preliminary experiment and results are shown to demonstrate the merit of the introduced navigation control algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.89-101
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• 2015

This paper proposes a statistical model of 3-D positions when tracking moving targets using the uncooled infrared (IR) stereo camera system. The proposed model is derived from two errors. One is the position error which is caused by the sampling pixels in the digital image. The other is the timing jitter which results from the irregular capture-timing in the infrared cameras. The capture-timing in the IR camera is measured using the jitter meter designed in this paper, and the observed jitters are statistically modeled as Gaussian distribution. This paper derives an integrated probability distribution by combining jitter error with pixel position error. The combined error is modeled as the convolution of two error distributions. To verify the proposed statistical position error model, this paper has some experiments in tracking moving objects with IR stereo camera. The 3-D positions of object are accurately measured by the trajectory scanner, and 3-D positions are also estimated by stereo matching from IR stereo camera system. According to the experiments, the positions of moving object are estimated within the statistically reliable range which is derived by convolution of two probability models of pixel position error and timing jitter respectively. It is expected that the proposed statistical model can be applied to estimate the uncertain 3-D positions of moving objects in the diverse fields.