• Journal of Korean Society of Disaster and Security
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• v.11 no.2
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• pp.69-74
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• 2018

Fog to which environmental impacts are sensitive has a danger to the safety of citizens due to the difficulty in predicting the specific area/time zone. Therefore, we propose a white smoke fog reduction technique using a fog removal device that can remove fog particles directly through dry air and anionic condensation nucleus instead of conventional passive countermeasures. In this study, to verify the effect of reducing fog and the effect of temperature on the white smoke fog which is frequently occurred in the detention basin. As a result, the visible distance of 100m or more was secured within 30 seconds, and it was confirmed that the fog reduction effect is more effective. Also, the lower the temperature, the larger the amount of white smoke fog was. However, the effect of reducing the white smoke fog by temperature was insignificant. Through this experiment, it was possible to verify the reduction effect of the white smoke fog generated in the detention basin through fog removal device.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.819-824
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• 2021

As technologies related to image processing such as autonomous driving and CCTV develop, fog removal algorithms using a single image are being studied to improve the problem of image distortion. As a method of predicting fog density, there is a method of estimating the depth of an image by generating a depth map, and various fog features may be used as training data of the depth map. In addition, it is essential to implement a hardware capable of processing high-definition images in real time in order to apply the fog removal algorithm to actual technologies. In this paper, we implement NLCV (Normalize Local Coefficient of Variation), a feature of fog based on coefficient of variation, in hardware. The proposed hardware is an FPGA implementation of Xilinx's xczu7ev-2ffvc1156 as a target device. As a result of synthesis through the Vivado program, it has a maximum operating frequency of 479.616MHz and shows that real-time processing is possible in 4K UHD environment.

• 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.