• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.2
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• pp.115-123
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• 2018

In a long-span bridge, the cables are important elements that support the load of the bridge. Accordingly, the cable tension is a very important variable in evaluating the health and safety of the bridge. The most popular methods of estimating the cable tensions are the direct method, which directly measures the cable stresses using load cells, hydraulic jacking devices, etc., and the vibration method, which inverses the tensions using the cable shapes and the measured dynamic characteristics. Studies on the use of the electromagnetic (EM) sensor, which detects the magnetic field variations caused by the change in the stress of the steel in the cable, are increasing. In this study, the lift-off test, the EM sensor, and the vibration method (Vision-based System and Accelerometer) were used to measure cable tension, and their results were compared and analyzed.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.27-34
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• 2013

Background subtraction is one of the key techniques for automatic video content analysis, especially in the tasks of visual detection and tracking of moving object. In this paper, we present a new sample-based technique for background extraction that provides background image as well as background model. To handle both high-frequency and low-frequency events at the same time, multiple interval background models are adopted. The main innovation concerns the use of a confidence factor to select the best model from the multiple interval background models. To our knowledge, it is the first time that a confidence factor is used for merging several background models in the field of background extraction. Experimental results revealed that our approach based on multiple interval sampling works well in complicated situations containing various speed moving objects with environmental changes.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.49-61
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• 2006

The lifting scheme has been found to be a flexible method for constructing scalar wavelets with desirable properties. In this paper, it is extended to the UDAR data compression. A newly developed data compression approach to approximate the UDAR surface with a series of non-overlapping triangles has been presented. Generally a Triangulated Irregular Networks (TIN) are the most common form of digital surface model that consists of elevation values with x, y coordinates that make up triangles. But over the years the TIN data representation has become an important research topic for many researchers due its large data size. Compression of TIN is needed for efficient management of large data and good surface visualization. This approach covers following steps: First, by using a Delaunay triangulation, an efficient algorithm is developed to generate TIN, which forms the terrain from an arbitrary set of data. A new interpolation wavelet filter for TIN has been applied in two steps, namely splitting and elevation. In the splitting step, a triangle has been divided into several sub-triangles and the elevation step has been used to 'modify' the point values (point coordinates for geometry) after the splitting. Then, this data set is compressed at the desired locations by using second generation wavelets. The quality of geographical surface representation after using proposed technique is compared with the original UDAR data. The results show that this method can be used for significant reduction of data set.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.379-388
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• 2019

Recently, a technique for acquiring spatial information data using UAV (Unmanned Aerial Vehicle) has been greatly developed. It is a very crucial issue of the GIS (Geographic Information System) mapping system that passes way point in the unmanned airframe and finally measures the accurate image and stable localization to the desired destination. Though positioning using DGPS (Differential Global Navigation System) or RTK-GPS (Real Time Kinematic-GPS) guarantee highly accurate, they are more expensive than the construction of a single positioning system using a single GPS. In the case of a low-priced single GPS system, the stability of the positioning data deteriorates. Therefore, it is necessary to supplement the uncertainty of the absolute position data of the UAV and to improve the accuracy of the current position data economically in the operating state of the UAV. The aim of this study was to present an algorithm enhancing the stability of position data in a single GPS mode of UAV with multiple GPS. First, the arrangement of multiple GPS receivers through the center of gravity of the UAV were examined. Next, MD (Mahalanobis Distance) is applied to detect instantaneous errors of GPS data in advance and eliminate outliers to increase the accuracy of previously collected multiple GPS data. Processing procedure for multiple GPS reception data by applying the center of the triangular method were presented to improve the position accuracy. Second, UAV navigation systems integrated multiple GPS through configuration of the UAV specifications were implemented. Using the unmanned airframe equipped with multiple GPS receivers, GPS data is measured with the TCM (Triangular Center Method). In addition, UAV equipped with multiple GPS were operated in study area and locational accuracy of multiple GPS of UAV with VRS (Virtual Reference Station) GNSS surveying were compared. The result showed that the error factors are compensated, and the error range are reduced, resulting in the reliability of the corrected value. In conclusion, the result in this paper is expected to realize high-precision position estimation at low cost in UAV using multiple low-cost GPS receivers.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.1
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• pp.23-27
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• 2019

In this paper, we propose a micro vibro tomography(MVT) method, that can be used to visualize two-dimensional cross-sectional images and micro-vibration tomographic images in real time in a non-contact and non-destructive manner. The proposed method is based on the optical coherence tomography(OCT) technique, with an additionally customized image processing algorithm. The proposed method can detect the micro-motions or vibrations in sample structures by measuring the phase shift variations in the sample structures. In this study, we show the potential capabilities of the proposed MVT system for measuring the micro-vibrations generated when sound waves in a frequency range of 2~5 kHz are applied to an $80-{\mu}m$ thick latex phantom, which mimics the changes in physical structure of the human tympanic membrane while hearing. Additionally, three-dimensional volumetric images of the MVT method were recorded to observe the surface morphological changes in the surface of the phantom sample which mimics the human tympanic membrane while hearing.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.6_2
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• pp.1043-1050
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• 2020

In this study, a study was presented on the monitoring technique of landslide area using UAV. In the case of disaster investigation using drone mapping, it can be used at various disaster sites. The mission can be carried out at various disaster sites, including surveys of damage to mountainous areas caused by landslides, building collapses surveys of flood damage, typhoons, earthquakes. The damage investigation plan using drone mapping is expected to be highly utilized at disaster sites where investigators cannot access it like in mountainous areas and where it is difficult to conduct direct damage investigations at the site. Drone mapping technology has many advantages in terms of disaster follow-up, such as recovery. Compared to the existing survey system, which was mainly carried out manually, the investigation time can be drastically reduced, and it can also respond to disaster sites that are difficult to carry out or are difficult to access directly. In addition, it is possible to establish and guide spatial data at the disaster site based on accurate mapping data from the time of the disaster, which has considerable strength in managing the situation of the disaster site, selecting priority areas for recovery, and establishing recovery plans. As such, drone mapping is a technology that can be used in a wide range of sites along with natural disasters and social disasters. If a damage investigation system is established through this, it is believed that it will contribute significantly to the rapid establishment of recovery plans along with the investigation of disaster response time and extent of damage recovery.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1026-1031
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• 2021

With the development of global automotive technology and the expansion of market size, demand for vehicles is increasing, which is leading to a decrease in the number of passengers on the road and an increase in the number of vehicles on the road. This causes traffic jams, and in order to solve these problems, the number of illegal vehicles continues to increase. Various technologies are being studied to crack down on these illegal activities. Previously developed systems use trigger equipment to recognize vehicles and photograph vehicles using infrared cameras to detect the number of passengers on board. In this paper, we propose a vehicle occupant detection system with deep learning model techniques without exploiting existing system-applied trigger equipment. The proposed technique proposes a system to detect vehicles by establishing triggers within images and to apply deep learning object recognition models to detect real-time boarding personnel.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.2_1
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• pp.177-184
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• 2022

The automatic defect sorting function of machinery parts is being introduced to the automation of the manufacturing process. In the final stage of automation of the manufacturing process, it is necessary to apply computer vision rather than human visual judgment to determine whether there is a defect. In this paper, we introduce a deep learning method to improve the classification performance of typical mechanical parts, such as welding parts, galvanized round plugs, and electro galvanized nuts, based on the results of experiments. In the case of poor welding, the method to further increase the depth of layer of the basic deep learning model was effective, and in the case of a circular plug, the surrounding data outside the defective target area affected it, so it could be solved through an appropriate pre-processing technique. Finally, in the case of a nut plated with zinc, since it receives data from multiple cameras due to its three-dimensional structure, it is greatly affected by lighting and has a problem in that it also affects the background image. To solve this problem, methods such as two-dimensional connectivity were applied in the object segmentation preprocessing process. Although the experiments suggested that the proposed methods are effective, most of the provided good/defective images data sets are relatively small, which may cause a learning balance problem of the deep learning model, so we plan to secure more data in the future.

• Journal of the Korean Society of Propulsion Engineers
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• v.26 no.1
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• pp.47-59
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• 2022

Four swirl coaxial injectors with different recess lengths were manufactured using an additive manufacturing method. Single-injection and bi-injection cold-flow experiments were performed using water and air as simulated propellants in an atmospheric pressure environment. According to the recess length and propellant flow conditions, the injection pressure drop and discharge coefficient were investigated, and the breakup length and spray angle were measured using an image processing technique. In the bi-injection pressure drop and discharge coefficient results, the liquid-side injector was not affected by the recess. For the gas-side injector, however, the injection pressure drop increased and the discharge coefficient decreased as the recess length increased. The breakup length in the single-injection increased with the increase of the recess, but decreased in the bi-injection.

• Imaging Science in Dentistry
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• v.52 no.3
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• pp.303-308
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• 2022

Purpose: This technical report aims to describe and detail the use of micro-computed tomography for a reliable evaluation of the bulk-fill composite/tooth interface. Materials and Methods: Bulk-fill composite restorations in tooth cavities were scanned using micro-computed tomography to obtain qualitatively and quantitatively valuable information. Two-dimensional information was processed using specific algorithms, and ultimately a 3-dimensional (3D) specimen reconstruction was generated. The 3D rendering allowed the visualization of voids inside bulk-fill composite materials and provided quantitative measurements. The 3D analysis software VG Studio MAX was used to perform image analysis and assess gap formation within the tooth-restoration interface. In particular, to evaluate internal adaptation, the Defect Analysis addon module of VG Studio Max was used. Results: The data, obtained with the processing software, highlighted the presence and the shape of gaps in different colours, representing the volume of porosity within a chromatic scale in which each colour quantitatively represents a well-defined volume. Conclusion: Micro-computed tomography makes it possible to obtain several quantitative parameters, providing fundamental information on defect shape and complexity. However, this technique has the limit of not discriminating materials without radiopacity and with low or no filler content, such as dental adhesives, and hence, they are difficult to visualise through software reconstruction.