• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1248-1254
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• 2022

Efforts are being made to prevent traffic accidents in the school zone in advance. However, traffic accidents in school zones continue to occur. If the driver can know the situation information in the child protection area in advance, accidents can be reduced. In this paper, we design a camera that eliminates blind spots in school zones and a number recognition camera system that can collect pre-traffic information. It is designed by improving the LIDAR system that recognizes vehicle speed and pedestrians. It collects and processes pedestrian and vehicle image information recognized by cameras and LIDAR, and applies artificial intelligence time series analysis and artificial intelligence algorithms. The artificial intelligence traffic accident prevention system learned by deep learning proposed in this paper provides a forced push service that delivers school zone information to the driver to the mobile device in the vehicle before entering the school zone. In addition, school zone traffic information is provided as an alarm on the LED signboard.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1874-1881
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• 2021

Black ice, which occurs mainly on the road, vehicle traffic bridges and tunnel entrances due to the sub-zero temperature due to the slip of the road due to heavy snow, is not recognized because the image of asphalt is transmitted in the driver's view, so the vehicle loses braking power because it causes serious loss of life and property. In this paper, we propose a method to identify the black ice by using infrared camera and to identify the road condition by using deep learning to compensate for the disadvantages of existing black ice detection methods (artificial satellite imaging, checking the pattern of slip by ultrasonic reception, measuring the temperature of the road surface, and checking the difference in friction force of the tire during vehicle driving) and to reduce the size of the sensor to detect black ice.

• Journal of IKEEE
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• v.26 no.3
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• pp.401-407
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• 2022

Recently, image processing technology for autonomous driving by recognizing objects and lanes through camera images to realize autonomous vehicles is being studied. Haze reduces the visibility of images captured by the camera and causes malfunctions of autonomous vehicles. To solve this, it is necessary to apply the haze removal function that can be processed in real time to the camera. Therefore, in this paper, the fog removal method of Sim with excellent performance is implemented with hardware capable of real-time processing. The proposed hardware was designed using Verilog HDL, and FPGA was implemented by setting Xilinx's xc7z045-2ffg900 as the target device. As a result of logic synthesis using Xilinx Vivado program, it has a maximum operating frequency of 276.932MHz and a maximum processing speed of 31.279fps in a 4K (4096×2160) high-resolution environment, thus satisfying the real-time processing standard.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.953-958
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• 2022

Holographic Stereogram can provide the depth perception without the visual fatigue and dizziness because it use multiple images acquired from the multiple viewpoints. In order to produce a holographic stereogram, it is necessary to obtain perspective images of a live object and record it on film using a digital hologram printer. when acquiring perspective images, the hologram without distortion can be produced only when the perspective images with a constant distance between the camera and the target is obtained. If the target is small, it is possible to keep the constant distance from the camera to object. but if it is large, this is difficult to keep the constant distance. In this study, we photograph the large object using the POI (Point of Interest) function which is one of the smart flight modes of drone to produce perspective images required for the hologram production. after that, problems such as the unexpected shakings and distance change between camera and object is corrected in post production. as a result, we produce the perspective images.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.197-205
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• 2024

Development of AI and big data-based algorithms to advance and optimize the recognition and detection performance of various static/dynamic vehicles in front and around the vehicle at a time when securing driving safety is the most important point in the development and commercialization of autonomous vehicles. etc. are being studied. However, there are many research cases for recognizing the same vehicle by using the unique advantages of radar and camera, but deep learning image processing technology is not used, or only a short distance is detected as the same target due to radar performance problems. Therefore, there is a need for a convergence-based vehicle recognition method that configures a dataset that can be collected from radar equipment and camera equipment, calculates the error of the dataset, and recognizes it as the same target. In this paper, we aim to develop a technology that can link location information according to the installation location because data errors occur because it is judged as the same object depending on the installation location of the radar and CCTV (video).

• Korean Journal of Optics and Photonics
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• v.35 no.4
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• pp.164-169
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• 2024

We applied recursive numerical computation to create a basic design of a camera optical module for mobile phones. To enhance the resolution performance for a 38-degree field of view, we constructed the optical system with six non-spherical lenses. However, to increase its applicability to a compact mobile phone, we limited the overall length to 5 mm in the design. Using the data obtained from the basic design, we proceeded with optimization design using the Zemax design tool. The optimized optical system achieved a resolution performance with a modulation transfer function value of more than 19% for a 280 lines/mm pattern and image distortion within 1.0% for all wavelength rays. In this paper, we verify the feasibility of using recursive numerical computation for the basic design of a compact mobile phone camera.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.2
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• pp.157-163
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• 2007

Recently, industrialization of a country is accelerated and request of society infrastructure is raised so national land development is activity view. Accordingly, the search for a wide-ranging buried heritage do acted in large construction region. Because the buried heritage get buried in land that it is necessary to the precision search and research for a record and a preservation. Until now, Surveying techniques of a historic site have made status map, profile and cross section map through leveling survey, total-station survey and sketch of specialist. So, to solve problems existing relic survey or drawing making method have using digital camera these researches rapidly and economically obtain stereo image of object and present a technique that constructs 3D image model for digital photogrammetry method. Also, these researches construct 3D image model for record and preservation of a historic site through site test and in 3D and graphical express a historic site and support works that produce other maps if we need it. offer base data of GIS (Geographic Information System) to collect and analyze overall, information of a historic site.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.834-841
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• 2004

There can be lips transformed geometrically in the lip images according to the location or the pose of camera and speaker. This transformation of the lip images changes geometric information of original lip phases. Therefore, for enhancing global lip information by using partial information of lips to correct lip phases transformed geometrically, in this paper we propose a method that can geometrically correct lips. The method is composed of two steps - the feature-deciding step and the correcting step. In the former, it is for us to extract key points and features of source image according to the its lip model and to create that of target image according to the its lip model. In the latter, we decide mapping relation after partition a source and target image based on information extracted in the previous step into each 4 regions. and then, after mapping, we unite corrected sub-images to a result image. As experiment image, we use fames that contain pronunciation on short vowels of the Korean language and use lip symmetry for evaluating the proposed algorithm. In experiment result, the correcting rate of the lower lip than the upper lip and that of lips moving largely than little was highly enhanced.

• Journal of the Korean Society for Marine Environment & Energy
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• v.14 no.4
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• pp.287-292
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• 2011

To evaluate the pressure-resistant performance of underwater equipment, hyperbaric chamber test facility which can make the hydrostatic pressure is used. In this test, strain gage is generally applied to measure the strain of object under test is suitable for measuring a tiny deformation, but it can not measure a large deformation. Thus this paper suggests a method to estimate the over -order deformation of object under test by the image processing with the image acquired from underwater camera in the hydrostatic test. The main procedure of suggested method comprises the first step to find significant points by processing the image two dimensionally and the second step to estimate a deformation of object under test by tracking the motion of these points. If completing the remained research which is estimating the deformation and comparing it with a real one, it can be a method to measure the over -order deformation of object under test.

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.146-153
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• 2018

This paper presents a superresolution demosaicing technique that can restore high-resolution color image from differently blurred low resolution images in Bayer domain. The proposed superresolution demosaicing algorithm uses an aperture mask wheel to get differently blurred low resolution images, so we just need to estimate point spread function at each frame. In addition, it does not require image registration because there is no translational motion between low resolution images. By using a rotatable aperture mask wheel, consecutive captured images provide sufficiently exclusive information for superresolution. Therefore, the proposed method can reduce the registration error between the low-resolution image as well as the calculation amount for superresolution restoration. The existing lens system of the camera can be extended to obtain a superresolution image by only adding an rotatable aperture mask wheels. Finally, in order to verify the performance of the proposed system, experimental results are performed. The proposed method showed the significant improvements in the sense of spatial and color resolution.