• Fire Science and Engineering
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• v.30 no.6
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• pp.92-98
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• 2016

This study evaluated thermal image real-time estimation and fire alarm using by a CCD camera, which has been a seamless feature-point analysis method, according to the angle and position and image fusion by a vector coordinate point set-up of equal shape. The system has higher accuracy, fixing data value of temperature sensing and fire image of 0~255, and sensor output-value of 0~5,000. The operation time of a flame specimen within 500 m, 1000 m, and 1500 m from the test report specimen took 7 s, 26 s, and 62 s, respectively, and image creation was proven. A diagnosis of fire accident was designated to 3 steps: Caution/Alarm/Fire. Therefore, a series of process and the transmission of SNS were identified. A light bulb and fluorescent bulb were also tested for a false alarm test, but no false alarm occurred. The possibility that an unwanted alarm will be reduced was verified through a forecast of the fire progress or real-time estimation of a thermal image by the change in the image of a time-based flame and an analysis of the diffusion velocity.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.1
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• pp.117-126
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• 2008

In this paper, it is presented a digital image processing method and the program (Visual C++) to determine the shape of the suspension bridge. To investigate the precision of this method, a suspension bridge is divided into 5, 13 and 19 images, respectively, by using the 6.3M pixels digital camera with 300mm zoom lens. Obtained results of the Kwang-Ahn Grand Bridge by using this method are fairly close to the real precision surveyed data. The accuracy is more improved by increasing the number of divided images of the structure. The total cost, man power and time of field survey by this method presented in this study could be much more reduced and the developed program could be applied with little modification for other structures like cable-stayed bridges, if lens compensation algorithms and program access capabilities are improved.

• Smart Structures and Systems
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• v.33 no.1
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• pp.55-64
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• 2024

This paper proposes a fusion imaging-based coating-defect classification method for steel structures that uses zero-shot learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured by an infrared (IR) camera, while photos of the coating surface are captured by a charge-coupled device (CCD) camera. The measured heat responses and visual images are then analyzed using zero-shot learning to classify the coating defects, and the estimated coating defects are visualized throughout the inspection surface of the steel structure. In contrast to older approaches to coating-defect classification that relied on visual inspection and were limited to surface defects, and older artificial neural network (ANN)-based methods that required large amounts of data for training and validation, the proposed method accurately classifies both internal and external defects and can classify coating defects for unobserved classes that are not included in the training. Additionally, the proposed model easily learns about additional classifying conditions, making it simple to add classes for problems of interest and field application. Based on the results of validation via field testing, the defect-type classification performance is improved 22.7% of accuracy by fusing visual and thermal imaging compared to using only a visual dataset. Furthermore, the classification accuracy of the proposed method on a test dataset with only trained classes is validated to be 100%. With word-embedding vectors for the labels of untrained classes, the classification accuracy of the proposed method is 86.4%.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.2
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• pp.148-156
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• 2007

The fiber dispersion in fiber-reinferced cementitious composites is a crucial factor with respect to achieving desired mechanical performance. However, evaluation of the fiber dispersion in the composite PVA-ECC (polyvinyl alcohol-engineered cementitious composite) is extremely challenging because of the low contrast of PVA fibers with the cement-based matrix. In the present work, a new evaluation method is developed and demonstrated. Using a fluorescence technique on the PVA-ECC, PVA fibers are observed as green dots in the cross-section of the composite. After capturing the fluorescence image with a charged couple device (CCD) camera through a microscope, the fiber dispersion is evaluated using an image processing technique and statistical tools. In this image processing technique, the fibers are more accurately detected by employing an enhanced algorithm developed based on a discriminant method and watershed segmentation. The influence of fiber orientation on the fiber dispersion evaluation was also investigated via shape analyses of fiber images.

• Journal of the Optical Society of Korea
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• v.15 no.2
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• pp.174-181
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• 2011

An airborne sensor is developed for remote sensing on an aerial vehicle (UV). The sensor is an optical payload for an eletro-optical/infrared (EO/IR) dual band camera that combines visible and IR imaging capabilities in a compact and lightweight package. It adopts a Ritchey-Chr$\'{e}$tien telescope for the common front end optics with several relay optics that divide and deliver EO and IR bands to a charge-coupled-device (CCD) and an IR detector, respectively. The EO/IR camera for dual bands is mounted on a two-axis gimbal that provides stabilized imaging and precision pointing in both the along and cross-track directions. We first investigate the mechanical deformations, displacements and stress of the EO/IR camera through finite element analysis (FEA) for five cases: three gravitational effects and two thermal conditions. For investigating gravitational effects, one gravitational acceleration (1 g) is given along each of the +x, +y and +z directions. The two thermal conditions are the overall temperature change to $30^{\circ}C$ from $20^{\circ}C$ and the temperature gradient across the primary mirror pupil from $-5^{\circ}C$ to $+5^{\circ}C$. Optical performance, represented by the modulation transfer function (MTF), is then predicted by integrating the FEA results into optics design/analysis software. This analysis shows the IR channel can sustain imaging performance as good as designed, i.e., MTF 38% at 13 line-pairs-per-mm (lpm), with refocus capability. Similarly, the EO channel can keep the designed performance (MTF 73% at 27.3 lpm) except in the case of the overall temperature change, in which the EO channel experiences slight performance degradation (MTF 16% drop) for $20^{\circ}C$ overall temperate change.

• Journal of Ocean Engineering and Technology
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• v.30 no.1
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• pp.44-50
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• 2016

An experimental study was performed to investigate the behavior of green water on a structure with a rectangular cross section under wave conditions, along with the flow characteristics in bubbly water flow. An experiment was conducted in a two-dimensional wave flume using an acrylic model (1/125) of FPSO BW Pioneer operating in the Gulf of Mexico under its design wave condition. The occurrence of green water, including its development, in front of the model was captured using a high-speed Charge Coupled Device (CCD) camera with the shadowgraph technique. Using consecutive images, the generation procedure for green water on the model was divided into five phases: flip through, air entrapment, wave run-up, wave overturning, and water shipping. In addition, the distinct water elevations of the green water were defined as the height of flip through, height of splashing jet, and height of freeboard exceedance, and showed a linear relationship with the incoming wave height.

• Journal of the Korean Society for Nondestructive Testing
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• v.19 no.4
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• pp.277-287
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• 1999

Quasi-static tests such as monotonic tension and loading/unloading tension were performed to investigate the bond characteristics and the failure processes for the T-joint specimens made from fiber/epoxy composite material. Two types of specimens, each consists of two components, e. g. skin and frame. were manufactured by co-curing and secondary bonding. During the monotonic tension test, AE instrument was used to predict AE signal at the initial and middle stage of the damage propagation. The damage initiation and progression were monitored optically using m (Charge Coupled Device) camera. And the internal crack front profile was examined using ultrasonic C-scan. The results indicate that the loads representing the abrupt increase of the AE signal are within the error range of 5 percent comparing to the loads shown in the load-time curve. Also it is shown that the initiation of crack occurred in the noodle region for both co-cured and secondarily bonded specimen. The final failure occurred in the noodle region for the co-cured specimen. but at the skin/frame termination point for the secondarily bonded specimen. Based on the results, it was found that two kinds of specimen show different failure modes depending on the manufacturing methods.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.68-79
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• 2008

Ground vehicle borne system which is named RoSSAV(Road Safety Survey and Analysis Vehicle) developed in KICT(Korea Institute of Construction Technology) can collect road geometric data. This system therefore is able to evaluate the road safety and analyze road deficient sections using data collected along the roads. The purpose of this study is to extract road geometric data for 3D road modeling in dangerous road section and The system should be able to quickly provide more accurate data. Various sensors(circular laser scanner, GPS, INS, CCD camera and DMI) are installed in moving object and collect road environment data. Finally, We extract 3d road geometry(center, boundary), road facility and slope using integrated multi-sensor data.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.12
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• pp.90-97
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• 1999

Recently, there have been many researches to automate processing and analysing image data in medical field, due to the advance of image processing techniques, the fast communication network and high performance hardware. In this paper, we design and implement the system based on the multi-layer neural network model to be able to analyze, differentiate and count blood cells in the peripheral blood image. To do these, we segment red and white-blood cell in blood image acquired from microscope with CCD(Charge-coupled device) camera and then apply the various feature extraction algorithms to classify. In addition to, we reduce multi-variate feature number using PCA(Principle Component Analysis) to construct more efficient classifier. So, in this paper, we are sure that the proposed system can be applied to a pathological guided system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.75-84
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• 2018

The purpose of this study is that the low-cost mobile mapping system using INS (Inertial Navigation System) based on MEMS (Micro Electro Mechanical System) could decipher the interpretation of road facility with the accuracy of x, y 0.546m plane error. Even though the MMS (Mobile Mapping System) technology as a new measurement technology has been used vividly to set up geographic information by some world leading surveying equipment manufacturers, the domestic technology is still in its beginning stage. Several domestic institutes and companies tried to catch up the leading technology but they just produced prototypes which needs more stabilization. Through this thesis, we developed low-cost mobile mapping system installed with INS based on MEMS after time synchronizing sensors for MMS such as LiDAR (Light Detection And Ranging), CCD (Charge Coupled Device), GPS/INS (Global Positioning System / Inertial Navigation System) and DMI (Distance Measurement Instrument).