• Journal of Broadcast Engineering
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• v.7 no.1
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• pp.2-9
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• 2002

Recently. VR( Virtual Reality) applications such as virtual studio and virtual character are wifely used In TV programs. and AR( Augmented Reality) applications are also belong taken an interest increasingly. This paper introduces a virtual screen system. which Is a new AR application for broadcasting. The virtual screen system is a real-time video augmentation system by tracking a chroma-patterned moving panel. We haute recently developed a virtual screen system.'K-vision'. Our system enables the user to hold and morse a simple panel on which live video, pictures of 3D graphics images can appear. All the Images seen on the panel change In the correct perspective, according to movements of the camera and the user holding the panel, in real-time. For the purpose of tracking janet. we use some computer vision techniques such as blob analysis and feature tracking. K-vision can work well with any type of camera. requiring no special add-ons. And no need for sensor attachments to the panel. no calibration procedures required. We are using K-vision in some TV programs such as election. documentary and entertainment.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.58-66
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• 2023

In this study, cable tension was measured using the vibration method, and a vision-based system was applied as a sensor to measure the displacement response of a cable in a non-contact method. In the vision-based system, the camera is installed in a location that considers the target structure and the field of view of the camera. However, it can be difficult to recognize the control points required to measure the displacement response of a structure as the target structure and other structures such as vehicles may be included in the image at the intended installation location. In this study, a distorted image including a vehicle shows inaccurate results in image analysis due to the installation position of the vision-based system. Accordingly, the image including the vehicle was eliminated by calculating the similarity between the two images. To verify the validity of the method of estimating the cable tension of cable-stayed bridges using the proposed method, the vibration method was applied to cable-stayed bridges in service to measure the tension.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.687-692
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• 2018

In this paper, the development of an automotive thermal imaging camera providing image information for ADAS (Advanced Driver Assist System) and autonomous vehicles is described and an improved technique to enhance the details of the image is proposed. Thermal imaging cameras are used in various fields, such as the medical, industrial and military fields, for the purpose of temperature measurement and night vision. In automobiles, they are utilized for night vision systems. For their utilization in ADAS and autonomous vehicles, appropriate image resolution and enhanced detail are required for object recognition. In this study, a $640{\times}480$ resolution thermal imaging camera that can be applied to automobiles is developed and the BDE (Block-Range Detail Enhancement) technique is applied to improve the details of the image. In order to improve the image detail obtained in various driving environments, the block-range values between the target pixel and the surrounding 8 pixels are calculated and classified into 5 levels. Then, different factors are added or subtracted to obtain images with high utilization. The improved technique distinguishes the dark part of the image by the resulting temperature difference of 130mK and shows an improvement in the fine detail in both the bright and dark parts of the image. The developed thermal imaging camera using the improved detail enhancement technique is applied to a test vehicle and the results are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2689-2708
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• 2016

Multi-camera systems which integrate two or more low-cost digital cameras are adopted to reach higher ground coverage and improve the base-height ratio in low altitude remote sensing. To guarantee accurate multi-camera integration, the geometric relationship among cameras must be determined through platform calibration techniques. This paper proposed a combined two-step platform calibration method. In the first step, the static platform calibration was conducted based on the stable relative orientation constraint and convergent conditions among cameras in static environments. In the second step, a dynamic platform self-calibration approach was proposed based on not only tie points but also straight lines in order to correct the small change of the relative relationship among cameras during dynamic flight. Experiments based on the proposed two-step platform calibration method were carried out with terrestrial and aerial images from a multi-camera system combined with four consumer-grade digital cameras onboard an unmanned aerial vehicle. The experimental results have shown that the proposed platform calibration approach is able to compensate the varied relative relationship during flight, acquiring the mosaicing accuracy of virtual images smaller than 0.5pixel. The proposed approach can be extended for calibrating other low-cost multi-camera system without rigorously mechanical structure.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.9 s.174
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• pp.85-92
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• 2005

This paper describes the recognition method of small-obstacles using a camera for a mobile robot in indoor environment. The technique of image processing using a camera has been widely used for an automaton of industrial system, an inspection of inferior goods, a lookout of an invader, and a vision sensor of intelligent robot. Mobile robot could meet small-obstacles such as a small plastic bottle of about 0.5 l in quantity, a small box of $7{\times}7{\times}7cm^3$ in volume, and so on in its designated path, and could be disturbed by them in the locomotion of a mobile robot. So, it is necessary to research on the recognition of small-obstacles using a camera and program. In this paper, 2-D image processing algorism and method fur recognition of small-obstacles using a camera for a mobile robot in indoor environment was developed. The characteristic test of the developed program to confirm the recognition of small-obstacles was performed. It is shown that the developed program could judge the size and the position of small-obstacles accurately.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.765-774
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• 2019

In this paper, we propose a point cloud matching algorithm for multiple RGB-D cameras. In general, computer vision is concerned with the problem of precisely estimating camera position. Existing 3D model generation methods require a large number of cameras or expensive 3D cameras. In addition, the conventional method of obtaining the camera external parameters through the two-dimensional image has a large estimation error. In this paper, we propose a method to obtain coordinate transformation parameters with an error within a valid range by using depth image and function optimization method to generate omni-directional three-dimensional model using 8 low-cost RGB-D cameras.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.774-784
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• 2017

Occupancy sensors installed in buildings and households turn off the light if the space is vacant. Currently PIR (pyroelectric infra-red) motion sensors have been utilized. Recently, the researches using camera sensors have been carried out in order to overcome the demerit of PIR that can not detect static people. If the tradeoff of cost and performance is satisfied, the camera sensors are expected to replace the current PIRs. In this paper, we propose vision sensor-based occupancy detection being composed of tracking, recognition and detection. Our softeware is designed to meet the real-time processing. In experiments, 14.5fps is achieved at 15fps USB input. Also, the detection accuracy reached 82.0%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.157-163
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• 2022

Recently, with the development of automation in the industrial field, research on anomaly detection is being actively conducted. An application for anomaly detection used in factory automation is camera-based defect inspection. Vision camera inspection shows high performance and efficiency in factory automation, but it is difficult to overcome the instability of lighting and environmental conditions. Although camera inspection using deep learning can solve the problem of vision camera inspection with much higher performance, it is difficult to apply to actual industrial fields because it requires a huge amount of normal and abnormal data for learning. Therefore, in this study, we propose a network that overcomes the problem of collecting abnormal data with 72 geometric transformation deep learning methods using only normal data and adds an outlier exposure method for performance improvement. By applying and verifying this to the MVTec data set, which is a database for auto-mobile parts data and outlier detection, it is shown that it can be applied in actual industrial sites.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.115-125
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• 2023

This paper relates to the development of CCTV camera posture calibration algorithm that can simultaneously collect traffic information such as traffic volume and speed in the state of view of the CCTV camera set for traffic monitoring. The developed autonomous posture calibration algorithm uses vehicle recognition and tracking techniques to identify the road, and automatically determines the angle of view for the operator's traffic surveillance and traffic information collection. To verify the performance of the proposed algorithm, a CCTV installed on site was used, and the results of the angle of view automatically calculated by the autonomous posture calibration algorithm for the angle of view set for traffic surveillance and traffic information collection were compared.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.87-102
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• 1999

We propose an algorithm for augmenting a real video sequence with views of graphics ojbects without metric calibration of the video camera by representing the motion of the video camera in projective space. We define a virtual camera, through which views of graphics objects are generated. attached to the real camera by specifying image locations of the world coordinate system of the virtual world. The virtual camera is decomposed into calibration and motion components in order to make full use of graphics tools. The projective motion of the real camera recovered from image matches has a function of transferring the virtual camera and makes the virtual camera move according to the motion of the real camera. The virtual camera also follows the change of the internal parameters of the real camera. This paper shows theoretical and experimental results of our application of non-metric vision to augmented reality.