• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.7
• /
• pp.279-286
• /
• 2021

Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.

• Korean Journal of Remote Sensing
• /
• v.34 no.6_3
• /
• pp.1351-1367
• /
• 2018

Image registration is an essential process for image fusion, change detection and time series analysis using multi-sensor images. For this purpose, we need to detect accurately the difference of scale and rotation between the multi-sensor images with difference spatial resolution. In this paper, we propose a new feature matching method using variable circular template for image registration between multi-resolution images. The proposed method creates a circular template at the center of a feature point in a coarse scale image and also a variable circular template in a fine scale image, respectively. After changing the scale of the variable circular template, we rotate the variable circular template by each predefined angle and compute the mutual information between the two circular templates and then find the scale, the angle of rotation and the center location of the variable circular template, respectively, in fine scale image when the mutual information between the two circular templates is maximum. The proposed method was tested using Kompsat-2, Kompsat-3 and Kompsat-3A images with different spatial resolution. The experimental results showed that the error of scale factor, the error of rotation angle and the localization error of the control point were less than 0.004, $0.3^{\circ}$ and one pixel, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.7
• /
• pp.387-392
• /
• 2019

A technique was researched to detect bolt looseness using a transfer impedance technique (the dual piezoelectric material technique) for monitoring the structural health of a bolt joint. In order to use the single piezoelectric material technique, an expensive impedance analyzer should be used. However, in the transfer impedance technique, low-cost fault detection can be performed using a general function generator and a digital multimeter. A steel plate frame test specimen composed of bolt joints was fabricated, and the tightening torques of the bolts were loosened step by step. By using the transfer impedance method, the damage index was obtained. It was found that the presence of faults could be reasonably estimated using the damage index, which increased with the degree of bolt looseness. An experiment was performed on the same specimen using the single piezoelectric material technique, and the results showed a similar tendency. It could be possible to estimate the damage of a bolt joint at low cost by eliminating the expensive impedance analyzer. This method could be used effectively for structural health monitoring after carrying out a study to estimate the fault location and severity.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.6
• /
• pp.77-83
• /
• 2020

The heat treatment facility is in a situation where the scope of application of the remote IOT system is expanding due to the harsh environment caused by high heat and long working hours among the root industries. In this heat treatment process environment, the IOT middleware is required to play a pivotal role in interpreting, managing and controlling data information of IoT devices (sensors, etc.). Until now, the system controlled by the heat treatment remotely was operated with the command of the operator's batch system without overall monitoring of the site situation. However, for the safety and precise control of the heat treatment facility, it is necessary to control various sensors and recognize the surrounding work environment. As a solution to this, the heat treatment safety support system presented in this paper proposes a support system that can detect the access of the work manpower to the heat treatment furnace through thermal image detection and operate safely when ordering work from a remote location. In addition, an OPEN CV-based deterioration analysis system using DNN deep learning network was constructed for faster and more accurate recognition than general fixed hot spot monitoring-based thermal image analysis. Through this, we would like to propose a system that can be used universally in the heat treatment environment and support the safety management specialized in the heat treatment industry.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.6
• /
• pp.175-182
• /
• 2020

The non-contact eye tracking is a nonintrusive human-computer interface providing hands-free communications for people with severe disabilities. Recently. it is expected to do an important role in non-contact systems due to the recent coronavirus COVID-19, etc. This paper proposes a novel approach for an eye mouse using an eye tracking method based on a context-aware based AdaBoost multi-region classifier and ASSL algorithm. The conventional AdaBoost algorithm, however, cannot provide sufficiently reliable performance in face tracking for eye cursor pointing estimation, because it cannot take advantage of the spatial context relations among facial features. Therefore, we propose the eye-region context based AdaBoost multiple classifier for the efficient non-contact gaze tracking and mouse implementation. The proposed method detects, tracks, and aggregates various eye features to evaluate the gaze and adjusts active and semi-supervised learning based on the on-screen cursor. The proposed system has been successfully employed in eye location, and it can also be used to detect and track eye features. This system controls the computer cursor along the user's gaze and it was postprocessing by applying Gaussian modeling to prevent shaking during the real-time tracking using Kalman filter. In this system, target objects were randomly generated and the eye tracking performance was analyzed according to the Fits law in real time. It is expected that the utilization of non-contact interfaces.

• Journal of Environmental Impact Assessment
• /
• v.30 no.4
• /
• pp.247-257
• /
• 2021

In this work, Iron Nano-Particles Impregnated BioChar/bead (INPBC/bead) soil amendment was developed to increase biochar's reactivity to As in soil and preventing possible wind loss. Prior to preparation of INPBC/bead, INPBC was produced utilizing lignocellulosic biomass and Fe(III) solution in a hydrothermal method, followed by a calcination process. Then, the bead type amendment, INPBC/bead was produced by cross-linking reaction of alginate with INPBC. FT-IR, XRD, BET, and SEM-EDS analyses were utilized to characterize the as-synthesised materials. The particle size range of INPBC/bead was 1-4 mm, and different oxygen-containing functional groups and Fe3O4 crystalline phase were produced on the surface of INPBC/bead, according to the characterization results. The soil cultivation test was carried out in order to assess the stabilization performance of INPBC/bead utilizing As and Pb-contaminated soil obtained from an abandoned mining location in South Korea. After 4 weeks of culture, TCLP and SPLP extraction tests were performed to assess the stabilization efficacy of the amendment. The TCLP and SPLP findings revealed that raising the application ratio improved stabilizing efficiency. The As stabilization efficiency was determined to be 81.56 % based on SPLP test findings for a 5% in (w/w) INPBC/bead treatment, and the content of Pb in extracts was reduced to the limit of detection. According to the findings of this study, INPBC/bead that can maintain pH of origin soil and minimize wind loss might be a potential amendment for soil polluted with As and heavy metals.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1479-1488
• /
• 2022

Accidents in which oil spills occur intermittently in the ocean due to ship collisions and sinkings. In order to prepare prompt countermeasures when such an accident occurs, it is necessary to accurately identify the current status of spilled oil. To this end, the Coast Guard patrols the target area with a fixed-wing airplane or helicopter and checks it with the naked eye or video, but it was difficult to determine the area contaminated by the spilled oil and its exact location on the map. Accordingly, this study develops a technology for direct ortho-rectification by automatically geo-referencing aerial images collected by the Coast Guard without individual ground reference points to identify the current status of spilled oil. First, meta information required for georeferencing is extracted from a visualized screen of sensor information such as video by optical character recognition (OCR). Based on the extracted information, the external orientation parameters of the image are determined. Images are individually orthorectified using the determined the external orientation parameters. The accuracy of individual orthoimages generated through this method was evaluated to be about tens of meters up to 100 m. The accuracy level was reasonably acceptable considering the inherent errors of the position and attitude sensors, the inaccuracies in the internal orientation parameters such as camera focal length, without using no ground control points. It is judged to be an appropriate level for identifying the current status of spilled oil contaminated areas in the sea. In the future, if real-time transmission of images captured during flight becomes possible, individual orthoimages can be generated in real time through the proposed individual orthorectification technology. Based on this, it can be effectively used to quickly identify the current status of spilled oil contamination and establish countermeasures.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_4
• /
• pp.1925-1934
• /
• 2022

Monitoring nuclear activity for inaccessible areas using remote sensing technology is essential for nuclear non-proliferation. In recent years, deep learning has been actively used to detect nuclear-activity-related small objects. However, high-resolution satellite imagery containing small objects can result in class imbalance. As a result, there is a performance degradation problem in detecting small objects. Therefore, this study aims to improve detection accuracy by analyzing the effect of the ratio of small objects related to nuclear activity in the input data for the performance of the deep learning model. To this end, six case datasets with different ratios of small object pixels were generated and a U-Net model was trained for each case. Following that, each trained model was evaluated quantitatively and qualitatively using a test dataset containing various types of small object classes. The results of this study confirm that when the ratio of object pixels in the input image is adjusted, small objects related to nuclear activity can be detected efficiently. This study suggests that the performance of deep learning can be improved by adjusting the object pixel ratio of input data in the training dataset.

• Journal of the Korean Geotechnical Society
• /
• v.38 no.12
• /
• pp.19-28
• /
• 2022

Cavities behind concrete walls can adversely affect the stability of structures. Thus study aims to detect cavities behind concrete structures using a microphone in a laboratory model test. A small-scale concrete wall is constructed in a chamber, which is composed of a reinforced concrete plate and dry soil. A plastic bowl is then placed between the plate and soil to simulate a cavity behind the concrete structure. Leaky surface acoustic waves are generated by impacting the concrete plate using a hammer and are measured using a microphone. The measured signals are analyzed using natural frequencies, and cavity-free sections are evaluated. The test results show that the first natural frequency decreases at the cavity section due to the flexural vibration behavior of the plate. In addition, the amplitude corresponding to the first natural frequency decreases as the measurement location becomes farther from the cavity center and significantly decreases at the measurement locations near the rebars. This study demonstrates that a microphone may be useful to detect cavities behind concrete walls.

• Economic and Environmental Geology
• /
• v.55 no.1
• /
• pp.111-125
• /
• 2022

Since landslide can cause huge damages to many facilities, close characterization of slopes is needed for appropriate reinforcements for the unstable ones in order to prevent the damages. Geophysical surveys, which can characterize a large area at a relatively low cost without disturbing slopes, have been widely employed for the assessment of slope stability in other countries. However, only conventional direct investigation methods are mainly used in Korea. In this paper, we analyzed various cases, which evaluated slope stabilities by characterizing slopes using geophysical exploration. First, we introduced changes in geophysical properties due to unstable media of slope like fracture location, fracture connectivity and distribution of groundwater level, and subsequently discussed the applicability of geophysical methods to the detection of the changes; the methods include electrical resistivity survey, seismic survey, self-potential survey, induced polarization survey and ground penetrating radar. Based on this description, we analyzed how geophysical surveys were performed on various slopes.