• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.35-41
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• 2016

In this paper, we propose a new real-time dead pixel detection method based on spatial compare filtering, which are usually used in the small target detection. Actually, the soft dead and the small target are cast in the same mold. Our proposed method detect and remove the dead pixels as applying the spatial compare filtering, into the pixel outputs of a detector after the non-uniformity correction. Therefore, we proposed method can effectively detect and replace the dead pixels regardless of the non-uniformity correction performance. In infrared camera, there are usually many dead detector pixels which produce abnormal output caused by manufactural process or operational environment. There are two kind of dead pixel. one is hard dead pixel which electronically generate abnormal outputs and other is soft dead pixel which changed and generated abnormal outputs by the planning process. Infrared camera have to perform non-uniformity correction because of structural and material properties of infrared detector. The hard dead pixels whose offset values obtained by non-uniformity correction are much larger or smaller than the average can be detected easily as dead pixels. However, some dead pixels(soft dead pixel) can remain, because of the difficulty of uncleared decision whether normal pixel or abnormal pixel.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.6
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• pp.579-589
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• 2008

In the past few years, there are many studies and researches of the underwater vehicles which are carried out its mission using sonar sensors. MSCL(Marine System Control Lab.) at Inha University developed test-bed small ROV, ISRO. ISRO is an open-frame type and has 4 thrusters. ISRO can control 4 motions i.e surge, sway, yaw and heave with sonar sensors. ISRO is developed for inspection of ship hull, marine structure, plant of lake or river and so on. When ROV ISRO inspects something, it is necessary to control the position of ROV ISRO's for the movement and anti-collision with structures in the underwater. In this paper, we deal with the development of a small ROV and verification of the position control system via simulation and experiment using sonar sensors.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.205-208
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• 2008

This article presents a methodology for the monitoring of air pollution. All over the world, the interest in the environment has been continuously increasing. Unfortunately, much of this interest is due to emerging problems, such as the greenhouse effect and climate change. For this reason, research into carbon dioxide, which causes the greenhouse effect, is progressing rapidly. This article presents a method of measuring the level of carbon dioxide and other substances in the air through the utilization of mobile-networking base stations and measured data. First of all, sensors are attached at the appropriate position of the mobile-networking base stations. These sensors will measure the air quality in their respective positions, and send sensor data to an urban management center via network gateways and data-collecting systems. The measured data can be used for various purposes. In general, it can be used to measure the air quality, which can then be used as a basis for urban planning. The method described herein utilizes airpollution sensors that are attached to the base stations in different locations and at varying heights. The data obtained hereby will be applicable in many fields. At this time this is simply a methodology, however we hope that it will lead to a practical application.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.351-360
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• 2022

Autonomous vehicles require precise knowledge of their position, velocity and orientation in all weather and traffic conditions in any time. And, these information is effectively used for path planning, perception, and control that are key factors for safety of vehicle driving. For this purpose, a high precision GNSS technology is widely adopted in autonomous vehicles as a core localization and navigation method. However, due to the lack of infrastructure as well as cost issue regarding GNSS correction data communication, only a few high precision GNSS technology will be available for future commercial autonomous vehicles. Recently, a high precision GNSS sensor that is based on a Broadcast-RTK system to dramatically reduce network maintenance cost by utilizing the existing broadcasting network is released. In this paper, we present the performance test result of the broadcast-RTK-based commercial high precision GNSS receiver to test the feasibility of the system for autonomous driving in Korea. Massive measurement campaigns covering of Korea region were performed, and the obtained measurements were analyzed in terms of ambiguity fixing rate, integer ambiguity loss recovery, time to retry ambiguity fixing, average correction information update rate as well as accuracy in comparison to other high precision systems.

• Korean Journal of Optics and Photonics
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• v.32 no.3
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• pp.108-113
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• 2021

We propose and experimentally demonstrate a method of remote sound extraction using laser Doppler interferometry. The output frequency of a laser Doppler interferometer changes to be the same as the frequency of the acoustic wave from than object vibrated by the sound due to the Doppler effect. Based on this phenomenon, we measure the vibrational frequency of a remote target affected by a sound wave in real time, via laser Doppler interferometry. We track the peak frequency of the interferometer's output via appropriate signal processing, which confirms that the characteristics of the so detected wave are the same as that of the original sound source. We also confirm that the same method can retrieve the sound waves not only from remote sources of single tones, but from those of any sound.

• The Journal of Korea Robotics Society
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• v.17 no.4
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• pp.417-424
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• 2022

In this paper, the developed trunk cargo unloading automation system is introduced, and the RGB-D sensor-based box loading situation recognition method and unloading plan applied to this system are suggested. First of all, it is necessary to recognize the position of the box in a truck. To do this, we first apply CNN-based YOLO, which can recognize objects in RGB images in real-time. Then, the normal vector of the center of the box is obtained using the depth image to reduce misrecognition in parts other than the box, and the inner wall of the truck in an image is removed. And a method of classifying the layers of the boxes according to the distance using the recognized depth information of the boxes is suggested. Given the coordinates of the boxes on the nearest layer, a method of generating the optimal path to take out the boxes the fastest using this information is introduced. In addition, kinematic analysis is performed to move the conveyor to the position of the box to be taken out of the truck, and kinematic analysis is also performed to control the robot arm that takes out the boxes. Finally, the effectiveness of the developed system and algorithm through a test bed is proved.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2004.11a
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• pp.122-125
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• 2004

In radiotherapy of tumors in liver, enough planning target volume (PTV) margins are necessary to compensate breathing-related movement of tumor volumes. To overcome the problems, this study aims to obtain patients' body movements by using a moving phantom and an ultrasonic sensor, and to develop respiration gating techniques that can adjust patients' beds by using reversed values of the data obtained. The phantom made to measure patients' body movements is composed of a microprocessor (BS II, 20 MHz, 8K Byte), a sensor (Ultra-Sonic, range 3 cm ${\sim}$3 m), host computer (RS232C) and stepping motor (torque 2.3Kg) etc., and the program to control and operate it was developed. The program allows the phantom to move within the maximum range of 2 cm, its movements and corrections to take place in order, and x, y and z to move successively. After the moving phantom was adjusted by entering random movement data(three dimensional data form with distance of 2cm), and the phantom movements were acquired using the ultra sonic sensor, the two data were compared and analyzed. And then, after the movements by respiration were acquired by using guinea pigs, the real-time respiration gating techniques were drawn by operating the phantom with the reversed values of the data. The result of analyzing the acquisition-correction delay time for the three types of data values and about each value separately shows that the data values coincided with one another within 1% and that the acquisition-correction delay time was obtained real-time (2.34 ${\times}$ 10$^{-4}$sec). This study successfully confirms the clinic application possibility of respiration gating techniques by using a moving phantom and an ultra sonic sensor. With ongoing development of additional analysis system, which can be used in real-time set-up reproducibility analysis, it may be beneficially used in radiotherapy of moving tumors.

• Radiation Oncology Journal
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• v.22 no.4
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• pp.316-324
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• 2004

Purpose : In radiotherapy of tumors in liver, enough planning target volume (PTV) margins are necessary to compensate breathing-related movement of tumor volumes. To overcome the problems, this study aims to obtain patients' body movements by using a moving phantom and an ultrasonic sensor, and to develop respiration sating techniques that can adjust patients' beds by using reversed values of the data obtained. Materials and Methods : The phantom made to measure patients' body movements is composed of a microprocessor (BS II, 20 MHz, 8K Byte), a sensor (Ultra-Sonic, range $3\~3$ m), host computer (RS232C) and stepping motor (torque 2.3 Kg) etc., and the program to control and operate it was developed. The program allows the phantom to move within the maximum range of 2 cm, its movements and corrections to take place In order, and x, y and z to move successively. After the moving phantom was adjusted by entering random movement data (three dimensional data form with distance of 2 cm), and the phantom movements were acquired using the ultra sonic sensor, the two data were compared and analyzed. And then, after the movements by respiration were acquired by using guinea pigs, the real-time respiration gating techniques were drawn by operating the phantom with the reversed values of the data. Results : The result of analyzing the acquisition-correction delay time the three types of data values and about each value separately shows that the data values coincided with one another within $1\%$ and that the acquisition-correction delay time was obtained real-time $(2.34{\times}10^{-4}sec)$. Conclusion : This study successfully confirms the clinic application possibility of respiration gating techniques by using a moving phantom and an ultrasonic sensor. With ongoing development of additional analysis system, which can be used in real-time set-up reproducibility analysis, it may be beneficially used in radiotherapy of moving tumors.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.56-76
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• 2022

This study shared with community mapping participants spatial analysis information, collected using smart devices, to give them an opportunity to objectively review their opinions. The study examined the impact of sharing such spatial information on residents' decision-making and perceptions. Yeongju-dong in Jung-gu district of Busan Metropolitan City, South Korea was selected for the case study; community mapping was carried out in Yeongju-dong to identify hazardous areas to improve pedestrian safety of primary school students. The community mapping participants drew a preliminary hazard map based on their experience and perception. Then, they drew a second hazard map after being given spatial information on pedestrian safety installations and pedestrian flow collected with smart devices including drones and sensors. Numerous changes in ranking across various sections occurred when the two maps were compared. There was a climb in the ranking of areas where the pedestrian flow was higher and lacked safety installations based on objective measurements over the perceptions of the participating people. Furthermore, according to a survey conducted among the participants, the provision of spatial analysis information using smart devices during community mapping process not only helped them recognize local community problems, but also raised their expectations that their submitted opinions would be reflected in policies. Moreover, the participants demonstrated increased self-confidence and faith in themselves as they were able to have more trust in the outcome they created.

• Journal of Korean Society of Rural Planning
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• v.30 no.1
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• pp.57-66
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• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.