• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.809-813
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• 2004

In this paper, we developed a network camera for CMOS camera module inspection. The design, implementation details including embedded linux porting and CPLD logics, and performance of network camera are described. The network camera consists of SoC(S3C4530A), CPLD and CMOS image sensor. In order to image data of CMOS image sensor we designed capture logics on CPLD by using VHDL program. Embedded Linux such as uClinux is performed on the network camera to utilize development environment and TCP/IP protocol specification. The application is based on socket communication between GUI on PC and Embedded Linux based network camera. When JPEG compression is applied, the transmission speed was improved enough for this system to be used for an alternative of expensive CCTV or remote monitoring system in a power plant and uninhabited places.

• Smart Structures and Systems
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• v.24 no.5
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• pp.587-595
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• 2019

Deformation measurement of large scale structures, such as the ground beds of high-rise buildings, tunnels, bridge, and railways, are important for insuring service quality and safety. The pose-relay videometrics method and displacement-relay videometrics method have already presented to measure the pose of non-intervisible objects and vertical subsidence of unstable areas, respectively. Both methods combine the cameras and cooperative markers to form the camera series networks. Based on these two networks, we propose two novel videometrics methods with closed-loop camera series network for deformation measurement of large scale structures. The closed-loop camera series network offers "closed-loop constraints" for the camera series network: the deformation of the reference points observed by different measurement stations is identical. The closed-loop constraints improve the measurement accuracy using camera series network. Furthermore, multiple closed-loops and the flexible combination of camera series network are introduced to facilitate more complex deformation measurement tasks. Simulated results show that the closed-loop constraints can enhance the measurement accuracy of camera series network effectively.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.510-514
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• 1994

This paper deals with an application of neural network to camera calibration with wide angle lens and 2-D range finding. Wide angle lens has an advantage of having wide view angles for mobile environment recognition ans robot eye in hand system. But, it has severe radial distortion. Multilayer neural network is used for the calibration of the camera considering lens distortion, and is trained it by error back-propagation method. MLP can map between camera image plane and plane the made by structured light. In experiments, Calibration of camers was executed with calibration chart which was printed by using laser printer with 300 d.p.i. resolution. High distortion lens, COSMICAR 4.2mm, was used to see whether the neural network could effectively calibrate camera distortion. 2-D range of several objects well be measured with laser range finding system composed of camera, frame grabber and laser structured light. The performance of 3-D range finding system was evaluated through experiments and analysis of the results.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.2
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• pp.133-139
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• 2010

PC camera-based instant messenger have problems of video image break/delay and noise. The reason is caused by a composed problem that PC Camera is belong to the connected PC and operating in the PC. This research suggests an instant messenger that uses network camera connected to LAN instead of PC camera. Therefore, the instant messenger has a component that the camera is separated from PC. This research designs sequence diagram, video calls flow chart, and graphic user interface of the instant messenger. The instant messenger based on network camera provides high quality video calls service and makes it possible to call from a special remote site with real-time video image.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.182-186
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• 2019

When a camera is employed for 3D sensing, accurate camera calibration is vital as it is a prerequisite for the subsequent steps of the sensing process. Camera calibration is usually performed by complex mathematical modeling and geometric analysis. On the other contrary, data learning using an artificial neural network can establish a transformation relation between the 3D space and the 2D camera image without explicit camera modeling. However, a neural network requires a large amount of accurate data for its learning. A significantly large amount of time and work using a precise system setup is needed to collect extensive data accurately in practice. In this study, we propose a two-step neural calibration method that is effective when only a small amount of learning data is available. In the first step, the camera projection transformation matrix is determined using the limited available data. In the second step, the transformation matrix is used for generating a large amount of synthetic data, and the neural network is trained using the generated data. Results of simulation study have shown that the proposed method as valid and effective.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.952-959
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• 2016

This paper proposes a novel indoor positioning system (IPS) that uses a calibrated camera sensor network and dense 3D map information. The proposed IPS information is obtained by generating a bird's-eye image from multiple camera images; thus, our proposed IPS can provide accurate position information when objects (e.g., the mobile robot or pedestrians) are detected from multiple camera views. We evaluate the proposed IPS in a real environment with moving objects in a wireless camera sensor network. The results demonstrate that the proposed IPS can provide accurate position information for moving objects. This can improve the localization performance for mobile robot operation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.151-152
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• 2009

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.476-481
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• 2008

The necessity of intelligent surveillance system is gradually considered seriously from the space where the security is important. From this paper will load Network Camera in Mobile Robot based on embedded Linux and Goal is in the system embodiment will be able to track the intruder. From Network Camera uses Wireless Lan transmits an image with server, grasps direction of the intruder used Block Matching algorithms from server, transmits direction information and tracks an intruder. The robot tracks the intruder according to gets the effective image of an intruder. In compliance with this paper the system which is embodied is linked with a different surveillance system and as intelligent surveillance system there is a possibility of becoming worse a reliability.

• The Research Journal of the Costume Culture
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• v.30 no.5
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• pp.766-778
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• 2022

Image-oriented information is becoming increasingly important on social networking services (SNS); the background of this trend is the popularity of selfies. Currently, camera applications using augmented reality (AR) and artificial intelligence (AI) technologies are gaining traction. An AR camera app is a smartphone application that converts selfies into various interesting forms using filters. In this study, we investigated the change of keywords according to the time flow of selfies in Goolgle News articles through semantic network analysis. Additionally, we examined the effects of using an AR camera app on appearance satisfaction and self-esteem when taking a selfie. Semantic network analysis revealed that in 2013, postings of specific people were the most prominent selfie-related keywords. In 2019, keywords appeared regarding the launch of a new smartphone with a rear-facing camera for selfies; in 2020, keywords related to communication through selfies appeared. As a result of examining the effect of the degree of use of the AR camera app on appearance satisfaction, it was found that the higher the degree of use, the higher the user's interest in appearance. As a result of examining the effect of the degree of use of the AR camera app on self-esteem, it was found that the higher the degree of use, the higher the user's negative self-esteem.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1617-1620
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• 1997

This paper describes the camera caliberation based-neural network with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distoriton causes an 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 aclibration is illustrated by simulation and experiment.