• Smart Structures and Systems
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• v.29 no.1
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• pp.141-151
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• 2022

In recent years, the industry and research communities have focused on developing autonomous crack inspection approaches, which mainly include image acquisition and crack detection. In these approaches, mobile devices such as cameras, drones or smartphones are utilized as sensing platforms to acquire structural images, and the deep learning (DL)-based methods are being developed as important crack detection approaches. However, the process of image acquisition and collection is time-consuming, which delays the inspection. Also, the present mobile devices such as smartphones can be not only a sensing platform but also a computing platform that can be embedded with deep neural networks (DNNs) to conduct on-site crack detection. Due to the limited computing resources of mobile devices, the size of the DNNs should be reduced to improve the computational efficiency. In this study, an architecture called pruned crack recognition network (PCR-Net) was developed for the detection of structural cracks. A dataset containing 11000 images was established based on the raw images from bridge inspections. A pruning method was introduced to reduce the size of the base architecture for the optimization of the model size. Comparative studies were conducted with image processing techniques (IPTs) and other DNNs for the evaluation of the performance of the proposed PCR-Net. Furthermore, a modularly designed framework that integrated the PCR-Net was developed to realize a DL-based crack detection application for smartphones. Finally, on-site crack detection experiments were carried out to validate the performance of the developed system of smartphone-based detection of structural cracks.

• Journal of Ocean Engineering and Technology
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• v.27 no.3
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• pp.22-28
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• 2013

This paper suggests a navigation information display system that is based on augmented reality technology. A navigator always has to confirm the information from marine electronic navigation devices and then compare it with the view of targets outside the windows. This "head down" posture causes discomfort and sometimes near accidents such as collisions or missing objects, because he or she cannot keep an eye on the front view of the windows. Augmented reality can display both virtual and real information in a single display. Therefore, we attempted to adapt AR technology to assist navigators. To analyze the outside view of the bridge window, various computer image processing techniques are required because the sea surface has many noises that disturb computer image processing for object detection, such as waves, wakes, light reflection, and so on. In this study, we investigated an analysis module to extract navigational information from images that are captured by a CCTV camera, and we validated our prototype.

• Journal of Environmental Science International
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• v.23 no.4
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• pp.571-584
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• 2014

The present study aims to apply a surface image velocimetry(SIV) system to video images captured with CCTV and estimate the flood discharge. The CCTV was installed at the Hancheon Bridge of the Han Cheon in Jeju Island for disaster surveillance, and seven flood events occurred in 2012 were used. During the image analyses, input parameters, interrogation areas and searching areas were determined with proper calibration procedures. To check for accuracy and applicability of SIV, the velocities and flood discharges estimated by SIV were compared with the measured ones by an electromagnetic surface velocimeter, Kalisto. The comparison results showed fairly good agreements. The RMSE(Root Mean Square Error) values between two instruments showed a range of 4.13 and 14.2, and the determination coefficients reached 0.75 through 0.85. It means that the SIV could be used as a good alternative method for other traditional velocity measuring instruments in measuring flood discharges.

• Journal of the Korean Society of Hazard Mitigation
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• v.5 no.1 s.16
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• pp.63-68
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• 2005

LSIV (Large Scale Image Velocimetry), a technique of image analysis on velocity measurement, was applied to a hydraulic model experiment of river confluence. The surface velocities measured by using LSIV showed similar results with the mean velocities by using a traditional velocimeter, While a general velocimeter can measure only local point velocity, LSIV can measure whole velocity field with one shot. When it is applied to river confluence or around a bridge pier where local flow is dominant, LSIV may be a powerful tool to measure velocity field.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.84-88
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• 1999

Recently, the necessity of accessing spatial data from remote computer via network has been increased as distributed spatial data have been increased due to their size and cost. Many methods have been used in recent years for transferring spatial data, such as socket, CORBA, HTTP, RPC, FTP, etc. In this paper, we propose spatial clearinghouse components to access distributed spatial data sources via CORBA and Internet. The spatial clearinghouse components are defined as OLE/COM components that enable users to access spatial data that meet their requests from remote computer. For reusability, we design the spatial clearinghouse with UML and implement it as a set of components. In order to enhance interoperability among different platforms in distributed computing environment, we adopt international standards and open architecture such as CORBA, HTTB, and OpenGIS Simple Features Specifications. There are two kinds of spatial clearinghouse: CORBA-based spatial clearinghouse and Internet-based spatial clearinghouse. The CORBA-based spatial clearinghouse supports COM-CORBA bridge to access spatial data from remote data providers that satisfy the OpenGIS Simple Features Specification for OLE/COM using COM and CORBA interfaces. The Internet-based spatial clearinghouse provides Web-service components to access spatial data from remote data providers using Web-browser.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.3025-3047
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• 2021

This paper presents the latest Ethernet standardization of in-vehicle network and the future trends of automotive Ethernet technology. The proposed system provides design and optimization algorithms for automotive networking technology related to AVB (Audio Video Bridge) technology. We present a design of in-vehicle network system as well as the optimization of AVB for automotive. A proposal of Reduced Latency of Machine to Machine (RLMM) plays an outstanding role in reducing the latency among devices. RLMM's approach to real-world experimental cases indicates a reduction in latency of around 41.2%. The setup optimized for the automotive network environment is expected to significantly reduce the time in the development and design process. The results obtained in the study of image transmission latency are trustworthy because average values were collected over a long period of time. It is necessary to analyze a latency between multimedia devices within limited time which will be of considerable benefit to the industry. Furthermore, the proposed reliable camera and video streaming through optimized AVB device settings would provide a high level of support in the real-time comprehension and analysis of images with AI (Artificial Intelligence) algorithms in autonomous driving.

• Cartoon and Animation Studies
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• s.20
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• pp.87-104
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• 2010

Animation creates meaning and affection by combinig image and sound like film. directed by Yuri Norstein is a good text for analyzing animation sound in that it combines image and various music and sound effects well. This study focuses on analyzing the way that sound function to make meaning in this text. Generally sound is categorized into dialogue, music, and sound effect. And animation has its own characteristic in each category. The voice for dialogue is created corresponding to the image of the character and the rhythm is very important in Animation. Plus Sound effect in animation can be said to mimic not just sound but also movement. This study analyzes sound based on three sound factors and the concepts of the point of listening, subjective sound, and sound bridge. Subjective sound using the point of listening of the wolf and the baby bestows a special position on the main characters in the text. It is the overall characteristic of the sound use of this text that the repetitive combination of sound and image, the linguistic and annotative function of sound effect, and comparatively conventional use of music and sound effect enhance the affection and readability.

• Korean Journal of Construction Engineering and Management
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• v.22 no.3
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• pp.31-39
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• 2021

The modular construction method is an off-site construction method using built-in structures from the manufacturing facilities. Modular construction is commonly applied to buildings which have relatively smaller and simpler structures than other types of buildings. Although modular building has emerged in the domestic construction industry as an alternative building strategy, previous researches on the environmental characteristics of modular building has not been comprehensively studied. Thus, this study empirically analyzed the insulation performance of thermal bridge and condensation parts of the modular buildings by using IR image analysis, Air-Surface Temperature Ratio method, and temperature difference ratio. The insulation performance analysis was conducted by comparing a modular building and a RC building in Seoul. The results shows that there was no significant difference between insulation performances of RC building and modular building. Furthermore

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.107-116
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• 2022

Recently, research has been actively conducted on the technology of inspection facilities through image-based analysis assessment of human-inaccessible facilities. This research was conducted to study the conditions of deep learning-based imaging data on bridges and to develop an evaluation prototype program for bridges. To develop a deep learning-based bridge damage detection prototype, the Semantic Segmentation model, which enables damage detection and quantification among deep learning models, applied Mask-RCNN and constructed learning data 5,140 (including open-data) and labeling suitable for damage types. As a result of performance modeling verification, precision and reproduction rate analysis of concrete cracks, stripping/slapping, rebar exposure and paint stripping showed that the precision was 95.2 %, and the recall was 93.8 %. A 2^nd performance verification was performed on onsite data of crack concrete using damage rate of bridge members.

• International Journal of Highway Engineering
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• v.13 no.4
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• pp.123-132
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• 2011

The purpose of this study is to calculate and propose rational multi-lane loading factors for bridge design considering the probability of simultaneous truck passing in adjacent lanes and real truck weights. The probability of simultaneous truck passing is calculated by analyzing video image taken at various locations in highways and national roads. Weigh-In-Motion system data at two locations are used, which is combined with the probability of multiple presence to calculate the multi-lane loading factors for typical 2 lane and 5 lane bridges. Statistical properties of multi-lane loading factors are also calculated assuming that locations for video images and WIM data represent the overall traffic condition in the country. Results are compared with various design codes in the world and they show that the values are between the current Korea Bridge Design Code and AASHTO LRFD specification or Eurocode and are similar to Canadian Code.