• Smart Structures and Systems
• /
• v.24 no.5
• /
• pp.607-616
• /
• 2019

The video deflectometer based on digital image correlation is a non-contacting optical measurement method which has become a useful tool for characterization of the vertical deflections of large structures. In this study, a novel imaging model has been established which considers the variations of pitch angles in the full image. The new model allows deflection measurement at a wide working distance with high accuracy. A monocular video deflectometer has been accordingly developed with an inclination sensor, which facilitates dynamic determination of the orientations and rotation of the optical axis of the camera. This layout has advantages over the video deflectometers based on theodolites with respect to convenience. Experiments have been presented to show the accuracy of the new imaging model and the performance of the monocular video deflectometer in outdoor applications. Finally, this equipment has been applied to the measurement of the vertical deflection of Yingwuzhou Yangtze River Bridge in real time at a distance of hundreds of meters. The results show good agreement with the embedded GPS outputs.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.10
• /
• pp.3608-3626
• /
• 2021

The detection of bolts is an important task in high-speed train inspection systems, and it is frequently performed to ensure the safety of trains. The difficulty of the vision-based bolt inspection system lies in small sample defect detection, which makes the end-to-end network ineffective. In this paper, the problem is resolved in two stages, which includes the detection network and cascaded classification networks. For small bolt detection, all bolts including defective bolts and normal bolts are put together for conducting annotation training, a new loss function and a new boundingbox selection based on the smallest axis-aligned convex set are proposed. These allow YOLOv3 network to obtain the accurate position and bounding box of the various bolts. The average precision has been greatly improved on PASCAL VOC, MS COCO and actual data set. After that, the Siamese network is employed for estimating the status of the bolts. Using the convolutional Siamese network, we are able to get strong results on few-shot classification. Extensive experiments and comparisons on actual data set show that the system outperforms state-of-the-art algorithms in bolt inspection.

• International conference on construction engineering and project management
• /
• 2024.07a
• /
• pp.487-493
• /
• 2024

Presently, prefabricated concrete panels are extensively employed in diverse construction projects across the globe due to their exceptional quality. To maintain the overall quality of these construction projects, it is crucial to ensure that the dimensions of precast concrete panels align with their designated design specifications. Therefore, it is essential to develop a methodology capable of quickly and accurately measuring the dimensions of precast concrete panels. Currently, there are many advanced technologies used to examine the dimensions of prefabricated concrete panels such as terrestrial laser scanning, which is prone to time consuming and cost inefficiencies. To address these limitations, this study suggests a computer vision-based approach that utilizes April Tag markers and images taken from a mobile phone to measure and evaluate the dimensions and quality of precast concrete panels. The proposed algorithm operates as follows: Initially, the RGB image coordinates are converted to the world coordinate systems using April tag markers. Following, the masks of the precast concrete components are extracted using the state-of-the-art Segment Anything Model (SAM). Finally, an algorithm based on image processing technique is developed to estimate the dimensional properties of precast concrete panels. The effectiveness of the proposed method is validated through preliminary experiments conducted in the field-scale precast slabs, and the result is evaluated by comparing to the manual measurement result.

• Journal of Korea Technology Innovation Society
• /
• v.12 no.1
• /
• pp.88-112
• /
• 2009

This study attempts to define IT high-level human resources and to investigate past IT high-level human resources development (HRD) policies in order to promote IT HRD policy efficiently. Benchmarking implications were derived from comparative studies of foreign high-level HRD policies and we suggest IT high-level HRD Policy in the framework of National Future Strategy. The results of this study are rich in implications for implementation of IT HRD related to national R&D road-map in the field of information technology, the supply spread maintenance and the vision change of high-level HRD to cultivate global competitiveness, IT-based Fusion Technology HRD, and R&D related HRD policies and action plans.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.11
• /
• pp.1720-1728
• /
• 2022

The industrial 4.0 era has been opened with the development of artificial intelligence technology, and the realization of smart farms incorporating ICT technology is receiving great attention in the livestock industry. Among them, the quality management technology of livestock products and livestock operations incorporating computer vision-based artificial intelligence technology represent key technologies. However, the insufficient number of livestock image data for artificial intelligence model training and the severely unbalanced ratio of labels for recognizing a specific defective state are major obstacles to the related research and technology development. To overcome these problems, in this study, combining oversampling and adversarial case generation techniques is proposed as a method necessary to effectively utilizing small data labels for successful defect detection. In addition, experiments comparing performance and time cost of the applicable techniques were conducted. Through experiments, we confirm the validity of the proposed methods and draw utilization strategies from the study results.

• International Journal of Internet, Broadcasting and Communication
• /
• v.10 no.1
• /
• pp.71-76
• /
• 2018

The technology convergence of television, communication, and computing devices enables the rich social and entertaining experience through Smart TV in personal living space. The powerful smart TV computing platform allows to provide various user interaction interfaces like IR remote control, web based control, body gesture based control, etc. The presently used smart TV interaction user control methods are not efficient and user-friendly to access different type of media content and services and strongly required advanced way to control and access to the smart TV with easy user interface. This paper propose the optical wireless communication (OWC) based remote controller design for Smart TV using smart device Flashlights. In this approach, the user smart device act as a remote controller with touch based interactive smart device application and transfer the user control interface data to smart TV trough Flashlight using visible light communication method. The smart TV built-in camera follows the optical camera communication (OCC) principle to decode data and control smart TV user access functions according. This proposed method is not harmful as radio frequency (RF) radiation does it on human health and very simple to use as well user does need to any gesture moves to control the smart TV.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.12 no.2
• /
• pp.127-138
• /
• 2012

In this paper, we propose a real-time virtual re-convergence hardware platform especially to reduce the visual fatigue caused by stereoscopy. Our unique idea to reduce visual fatigue is to utilize the virtual re-convergence based on the optimized disparity-map that contains more depth information in the negative disparity area than in the positive area. Our virtual re-convergence hardware platform, which consists of image rectification, disparity estimation, depth post-processing, and virtual view control, is realized in real time with 60 fps on a single Xilinx Virtex-5 FPGA chip.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.3 no.4
• /
• pp.244-250
• /
• 2008

This paper describes the design and implementation of an unmanned ground vehicle (UGV) and also estimates how well autonomous navigation and remote control of UGV can be performed through the optimized arbitration of several sensor data, which are acquired from vision, obstacle detection, positioning system, etc. For the autonomous navigation, lane detection and tracing, global positioning, and obstacle avoidance are necessarily required. In addition, for the remote control, two types of experimental environments are established. One is to use a commercial racing wheel module, and the other is to use a haptic device that is useful for a user application based on virtual reality. Experimental results show that autonomous navigation and remote control of the designed UGV can be achieved with more effectiveness and accuracy using the proper arbitration of sensor data and navigation plan.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1997.10a
• /
• pp.225-229
• /
• 1997

This paper describes the camera calibration based-neural network with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes and inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing. The performance of proposed camera calibration is illustrated by simulation and experiment.

• Ocean and Polar Research
• /
• v.28 no.2
• /
• pp.209-214
• /
• 2006

The East Sea Branch (ESB) of KORDI will be launched in 2008. She will take a role of monitoring the sea surface topography and temperature by satellites, short- and long-term sea levels by tide gauges, coastal currents and open-sea circulation by setting up coastal radars and mooring current-meters and acoustic equipments, as well as monitoring nearshore processes, coastal erosion and water pollution. A basic program of coastal zone management will help ocean-policy makers to set up right decisions based upon scientific background of the regional data in the East Sea. Networking among the neighboring countries around the sea will supply more useful information not only for experts but also for ordinary vacationers or fishermen. In order for this program to be successfully settled down during the next decade, it is necessary for a leader to have the right vision to attract more experts from global brain pools and to manage the ESB as a leading-edge observatory in the world. Details about this leading-edge operational program are introduced in the text.