• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.2
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• pp.199-206
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• 2015

In this study, a new diagnosis method which can predict the working states of a pipe or its element in realtime is proposed by using an artificial neural network. The displacement data of an inspection element of a piping system are obtained by the use of PIV (particle image velocimetry), and are used for teaching a neural network. The measurement system consists of a camera, a light source and a host computer in which the artificial neural network is installed. In order to validate the constructed monitoring system, performance test was attempted for two kinds of mobile phone of which vibration modes are known. Three values of acceleration (minimum, maximum, mean) were tested for teaching the neural network. It was verified that mean values were appropriate to be used for monitoring data. The constructed diagnosis system could monitor the operation condition of a gas pipe.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.3
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• pp.248-253
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• 2014

Camera calibration is an indispensable process for improving measurement accuracy in industry fields such as machine vision. However, existing calibration cannot be applied to the calibration of mid-wave and long-wave infrared cameras. Recently, with the growing use of infrared thermal cameras that can measure defects from thermal properties, development of an applicable calibration target has become necessary. Thus, based on heat conduction analysis using finite element analysis, we developed a calibration target that can be used with both existing visible cameras and infrared thermal cameras, by implementing optimal design conditions, with consideration of factors such as thermal conductivity and emissivity, colors and materials. We performed comparative experiments on calibration target images from infrared thermal cameras and visible cameras. The results demonstrated the effectiveness of the proposed calibration target.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.1
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• pp.9-17
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• 2005

The objective of the study is to extract information about the road surfaces to be studied by analyzing asphalt concrete-paved road surface images photographed with a digital video camera. To analyze the accuracy of road surface information gained using a digital imagery processing method, it was compared and analyzed with the outcomes of control surveying. As a result, an average error of 0.0427 m in the X-axis direction, that of 0.0527 m in the Y-axis direction, and that of 0.1539 m in the Z-axis direction were found, good enough for mapping at a scale of 1:1,000 or less and GIS data. Besides, information on road surface assessment factors such as crack ratio, the amount of rutting and profile index was gained by analyzing processed digital imagery. This information made it possible to conduct road surface assessment by generating PSI and MCI. As quality digital image information has been gathered from roads and stored, important fundamental data on PMS (Pavement Management System) will become available in the future.

• The Journal of Korea Robotics Society
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• v.7 no.4
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• pp.259-266
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• 2012

In these days, researches about underwater robots have been actively in progress for the purposes of ocean detection and resource exploration. Unlike general underwater robots such as ROV(Remotely Operated Vehicle) and AUV(Autonomous Underwater Vehicle) which have propellers, an articulated underwater robot which is called Crabster has been being developed in KORDI(Korea Ocean Research & Development Institute) with many cooperation organizations since 2010. The robot is expected to be able to walk and swim under the sea with its legs. Among many researching fields of this project, we are focusing on a swimming section. In order to find effective swimming locomotion for the robot, we approached this subject in terms of Biomimetics. As a model of optimized swimming organism in nature, diving beetles were chosen. In the paper, swimming motions of diving beetles were analyzed in viewpoint of robotics for applying them into the swimming motion of the robot. After modeling the kinematics of diving beetle through robotics engineering technique, we obtained swimming patterns of the one of living diving beetles, and then compared them with calculated optimal swimming patterns of a robot leg. As the first trial to compare the locomotion data of legs of the diving beetle with a robot leg, we have sorted two representative swimming patterns such as forwarding and turning. Experimental environment has been set up to get the motion data of diving beetles. The experimental equipment consists of a transparent aquarium and a high speed camera. Various swimming motions of diving beetles were recorded with the camera. After classifying swimming patterns of the diving beetle, we can get angular data of each joint on hind legs by image processing software, Image J. The data were applied to an optimized algorithm for swimming of a robot leg which was designed by robotics engineering technique. Through this procedure, simulated results which show trajectories of a robot leg were compared with trajectories of a leg of a diving beetle in desired directions. As a result, we confirmed considerable similarity in the result of trajectory and joint angles comparison.

• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.323-335
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• 2012

In this paper, we propose an AR(augmented reality) system using user's bare hand based on computer vision. It is important for registering a virtual object on the real input image to detect and track correct feature points. The AR systems with markers are stable but they can not register the virtual object on an acquired image when the marker goes out of a range of the camera. There is a tendency to give users inconvenient environment which is limited to control a virtual object. On the other hand, our system detects fingertips as fiducial features using adaptive ellipse fitting method considering the geometric characteristics of hand. It registers the virtual object stably by getting movement of fingertips with determining the shortest distance from a palm center. We verified that the accuracy of fingertip detection over 82.0% and fingertip ordering and tracking have just 1.8% and 2.0% errors for each step. We proved that this system can replace the marker system by tacking a camera projection matrix effectively in the view of stable augmentation of virtual object.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.374-376
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• 2018

In this study, we developed a mobile home robot using a face recognition method using a camera attached to a raspberry pie. It receives the real time image through the camera attached to the raspberry pie, recognizes the face of the person, and distinguishes the operation of the smart cool air temperature device according to the result. It is expected that the robot will be able to increase the energy utilization efficiency by allowing the robot to operate in cold and hot winds only where there is no human being, instead of operating the hot and cold air conditioner.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.512-514
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• 2004

The Electro-Optical Camera (EOC) is a high spatial resolution, visible imaging sensor which collects visible image data of the earth's sunlit surface and is the primary payload on KOMPSAT-l. The purpose of the EOC payload is to provide high resolution visible imagery data to support cartography of the Korean Peninsula. The EOC is a push broom-scanned sensor which incorporates a single nadir looking telescope. At the nominal altitude of 685Km with the spacecraft in a nadir pointing attitude, the EOC collects data with a ground sample distance of approximately 6.6 meters and a swath width of around 17Km. The EOC is designed to operate with a duty cycle of up to 2 minutes (contiguous) per orbit over the mission lifetime of 3 years with the functions of programmable gain/offset. The EOC has no pointing mechanism of its own. EOC pointing is accomplished by right and left rolling of the spacecraft, as needed. Under nominal operating conditions, the spacecraft can be rolled to an angle in the range from +/- 15 to 30 degrees to support the collection of stereo data. In this paper, the status of EOC such as temperature, dark calibration, cover operation and thermal control is checked and analyzed by continuously monitored state of health (SOH) data and image data during the mission life of 3 years. The aliveness of EOC and operation continuation beyond mission life is confirmed by the results of the analysis.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.69-76
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• 2007

The main stream of presentation is interrupted because of the direct manipulation of their PC frequently so as to control the screen and file open and so on. A variety of products have been developed to solve these inconveniences of the conventional laser beam pointer [LBP] by simply adding a mouse function to the previous LBP. However. the LBPs fully supporting a mouse function are not yet appeared. In this paper. we developed the LBP fully fulfilling a mouse function using mono-camera as well as a robust image processing and analyzed the position detection accuracy. Finally we verified the developed LBP does not only fulfill a mouse function but also solve the defects of the current laser pointer such as inconvenient installation and Position detection errors due to the illumination and viewing direction changes.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.69-75
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• 2014

Existing People Counting System using a single overhead mounted camera has limitation in object recognition and counting in various environments. Those limitations are attributable to overlapping, occlusion and external factors, such as over-sized belongings and dramatic light change. Thus, this paper proposes the new concept of People Counting System by Facial Age Group using two depth cameras, at overhead and frontal viewpoints, in order to improve object recognition accuracy and robust people counting to external factors. The proposed system is counting the pedestrians by five process such as overhead image processing, frontal image processing, identical object recognition, facial age group classification and in-coming/out-going counting. The proposed system developed by C++, OpenCV and Kinect SDK, and it target group of 40 people(10 people by each age group) was setup for People Counting and Facial Age Group classification performance evaluation. The experimental results indicated approximately 98% accuracy in People Counting and 74.23% accuracy in the Facial Age Group classification.

• Journal of Digital Contents Society
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• v.15 no.4
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• pp.457-464
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• 2014

Recently, interests in space information data are increasing due to the initiation of spatial information open platform service by the Ministry of Land, Infrastructure and Transport. The purpose of this study is optimizing management and storing of the texture data, one kinds of 3D-spatial data. First, extract 3D-spatial data through the aerial triangulation and 3D-writing using raw image taken with the Multi-directional aerial camera and the vertical aerial camera. And develop the method to create single texture data and related technique by align and place corresponding 3D-spatial data to optimal storage space. Through experiment, the results show effect of 8 times of storage capacity reduction compared to existing single-file storage method, additionally, new method can improve file management efficiency in comparison with multiple file storage method. The results of this study can be cornerstone of three-dimensional space information management when dealing with bulk data, and utilizations will be enhanced through the further studies and algorithm improvement.