• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.153-158
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• 2019

In this paper, we analyze the infrared feature for the small coast targets according to the surrounding environment for autonomous flight device equipped with an infrared imaging sensor and we propose Cross Duality of Neural Network (CR-DuNN) method which can classify the target and clutter in coastal environment. In coastal environment, there are various property according to diverse change of air temperature, sea temperature, deferent seasons. And small coast target have various infrared feature according to diverse change of environment. In this various environment, it is very important thing that we analyze and classify targets from the clutters to improve target detection accuracy. Thus, we propose infrared feature learning algorithm through LSTM neural network and also propose CR-DuNN algorithm that integrate LSTM prediction network with Du-CNN classification network to classify targets from the clutters.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.4
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• pp.93-100
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• 1998

Pyoelectric infrared detectors based on La-modified PbTiO3 (PLT) thin films have been fabricated by RF magnetron sputtering and micromachining technology. The detectors form Pb$_{1-x}$ La$_{x}$Ti$_{1-x}$ O$_{3}$ (x=0.05) thin film ferroelectric capacitors epitaxially grown by RF magnetron sputtering on Pt/MgO (100) substrate. The sputtered PLT thin film exhibits highly c-axis oriented crystal struture that no poling trealization for sensing applications is required. This is an essential factor to increase the yield for realization of an infrared image sensor. Micromachining technology is used to lower the thermal mass of the detector by giving maximum sensor efficiency. Polyimide is coated on top of the sensing elements to support the fragile structure and the backside of the MgO substrate is selectively eteched to reduce the heat loss. The sensing element exhibited a very high detectivity D* of 8.5*10$^{8}$ cm..root.Hz/W at room temperature and it is about 100 times higher than the case of micromachining technology is not used. a sensing system that detects the position as well as the existence of a human body is realized using the array sensor.sor.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.183-186
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• 1988

The problem addressed in this paper is the accurate tracting of a dynamic target using outputs from a forward - looking infrared(FLIR) sensor as measurements. The important variations are 1) the spread of the target intensity pattern in the FLIR image plane, 2) target motion characteristics, and 3) the rms value and both spartial and temporal correlation of the back - ground noise. Based on this insights. design modifications and on - line adaptation copabilities are incorporated to enable this type of filter track highly maneuverable targets such as air-to-air missiles, with spatially distributed and changing image intensity profiles, against, background clutter.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.293-298
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• 2023

The military is facing a continuous decrease in personnel, and in order to cope with potential accidents and challenges in operations, efforts are being made to reduce the direct involvement of personnel by utilizing the latest technologies. Recently, the use of various sensors related to Manned-Unmanned Teaming and artificial intelligence technologies has gained attention, emphasizing the need for flexible utilization methods. In this paper, we propose four dataset construction methods that can be used for effective training of robots that can be deployed in military operations, utilizing not only RGB image data but also data acquired from IR image sensors. Since there is no publicly available dataset that combines RGB and IR image data, we directly acquired the dataset within buildings. The input values were constructed by combining RGB and IR image sensor data, taking into account the field of view, resolution, and channel values of both sensors. We compared the proposed method with conventional RGB image data classification training using the same learning model. By employing the proposed image data fusion method, we observed improved stability in training loss and approximately 3% higher accuracy.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.71-78
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• 2017

Many studies have been implemented to manage solar plant being supplied widely in recent years. This study analyzed heat emission of solar cell using unmanned aerial vehicle(UAV)-based thermal infrared sensor, and major conclusions are as belows. Firstly, orthomosaic image and digital surface model(DSM) data were acquired using UAV-based RGB sensor, and solar light module layer necessary to analyze the heat emission of solar cell was constructed by these data. Also as a result of horizontal error into validation points using virtual reference service(VRS) survey for evaluating the location accuracy of solar light module layer, higher location accuracy could be acquired like standard error of $dx={\pm}2.4cm$ and $dy={\pm}3.2cm$. And this study installed rubber patch to test the heat emission of solar cell and could analyzed efficiently the location of rubber patch being emitted heat using UAV-based thermal infrared sensor. Also standard error showd as ${\pm}3.5%$ in analysis between calculated cell ratio by rubber patch and analyzed cell ratio by UAV-based thermal infrared sensor. Therefore, it could be efficiently analyzed to heat emission of solar cell using UAV-based thermal infrared sensor. Also efficient maintenance of solar plant could be possible through extracting the code of solar light module being emitted of heat automatically.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.337-351
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• 2004

Our laboratory originally developed the compact, multi-spectral, automatic aerial photographic system PKNU3 to allow greater flexibility in geological and environmental data collection. We are currently developing the PKNU3 system, which consists of a color-infrared spectral camera capable of simultaneous photography in the visible and near-infrared bands; a thermal infrared camera; two computers, each with an 80-gigabyte memory capacity for storing images; an MPEG board that can compress and transfer data to the computers in real-time; and the capability of using a helicopter platform. Before actual aerial photographic testing of the PKNU3, we experimented with each sensor. We analyzed the lens distortion, the sensitivity of the CCD in each band, and the thermal response of the thermal infrared sensor before the aerial photographing. As of September 2004, the PKNU3 development schedule has reached the second phase of testing. As the result of two aerial photographic tests, R, G, B and IR images were taken simultaneously; and images with an overlap rate of 70% using the automatic 1-s interval data recording time could be obtained by PKNU3. Further study is warranted to enhance the system with the addition of gyroscopic and IMU units. We evaluated the PKNU 3 system as a method of environmental remote sensing by comparing each chlorophyll image derived from PKNU 3 photographs. This appraisement was backed up with existing study that resulted in a modest improvement in the linear fit between the measures of chlorophyll and the RVI, NDVI and SAVI images stem from photographs taken by Duncantech MS 3100 which has same spectral configuration with MS 4000 used in PKNU3 system.

• Journal of Korea Multimedia Society
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• v.8 no.1
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• pp.46-55
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• 2005

In this paper, we realize the panoramic infrared warning system to detect the small threaten object and propose the infrared image enhancement method to improve the warning ability of this system. This system composes of the sense head unit, the signal processing unit, and so on. In the proposed system, the sense head unit acquires the panoramic IR image with 360 degree field of view(FOV) by rotating the thermal sensor. The signal processing unit divides panoramic image into four sub-images with 90 degree FOV and computes the adaptive plateau value by using statistical characteristics of each subimage. Then the histogram equalization is performed for each subimage by using the adaptive plateau value. We realize the signal Processing unit by using the DSP and FPGA to perform the proposed method in real time. Experimental results show that the proposed method has better discrimination and lower false alarm rate than the conventional methods in this warning system.

• Current Optics and Photonics
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• v.5 no.3
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• pp.298-305
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• 2021

Modern distance sensing methods employ various measurement principles, including triangulation, time-of-flight, confocal, interferometric and frequency comb. Among them, the triangulation method, with a laser light source and an image sensor, is widely used in low-cost applications. We developed an omnidirectional two-dimensional (2D) distance sensor based on the triangulation principle for indoor floor mapping applications. The sensor has a range of 150-1500 mm with a relative resolution better than 4% over the range and 1% at 1 meter distance. It rotationally scans a compact one-dimensional (1D) distance sensor, composed of a near infrared (NIR) laser diode, a folding mirror, an imaging lens, and an image detector. We designed the sensor layout and configuration to satisfy the required measurement range and resolution, selecting easily available components in a special effort to reduce cost. We built a prototype and tested it with seven representative indoor wall specimens (white wallpaper, gray wallpaper, black wallpaper, furniture wood, black leather, brown leather, and white plastic) in a typical indoor illuminated condition, 200 lux, on a floor under ceiling mounted fluorescent lamps. We confirmed the proposed sensor provided reliable distance reading of all the specimens over the required measurement range (150-1500 mm) with a measurement resolution of 4% overall and 1% at 1 meter, regardless of illumination conditions.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.1
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• pp.25-31
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• 2012

We propose a method for an indoor mobile robot to track user with infrared transmitter. Several infrared receivers attached around by the mobile robot enable the robot to determine the moving direction by comparing the received signal patterns. The cost of the proposed system is not only cheaper than ultrasonic system, image signal processing, RFID, and RSSI method, but also robust against environment change because any complex algorithm is not necessary. In the mobile robot, ultrasonic sensors are equipped to avoid obstacles located in the moving direction, and a simple algorithm is embedded to avoid the case of poor signal reception.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.122-127
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• 2016

This paper propose implementation method of SoC system for efficient depth image segmentation. SoC systems are combined platform in the form of the Software and Hardware IP. In order to perform effectively, the user to determine the operation of the configuration of each part. In this paper, we implemented a segmentation of depth images taken by the infrared sensor at APU of SoC system. The proposed method efficiently implements high performance and low power in SoC system. Proposed method that using software parts of SoC system is capable to use at several depth image processing systems.