• Journal of Fashion Business
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• v.23 no.1
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• pp.103-115
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• 2019

In this study, we provided examples of light emitting diodes (LEDS) in everyday sportswear and confirmed their usefulness to provide functionality, aesthetics, and entertainment. One type of sports jacket and one set of sportswear were designed and manufactured using LEDs and made available to the general public for use in daily life to provide functionality, aesthetics, and entertainment. To generate digital images, a textural design of a circuit image was developed and applied, and the LEDs were placed on the developed textile in an attempt to merge the LEDs with the design. The product was equipped with a tilt sensor and produced a randomly lighted jacket with LEDs that adjusted according to movement. The LEDs turned on in the desired location by lifting the arm during night sports activities. The tricolor of NEO PIXEL LEDs lit randomly and its rhythmical design could be maximized when moving or exercising outdoors, and also for entertainment. The role of creating interest for lively and unexpected pleasures and the aesthetic beauty of LED lights were also obtained. There was no inconvenience or restriction of movement by LEDs or internal structures using the hot-melting technique, and the removable attachment of the device made it easier to wash.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1229-1236
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• 2022

In this paper, we studied accident-aware smart streetlights to prevent secondary accidents when driving on highways. It used Arduino and sensors to inform drivers of weather conditions, incorporated functions such as LED brightness control according to sunlight and night driving vehicles, and used Raspberry Pi camera OpenCV to learn various traffic accidents, natural disasters, and wildlife.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.117-126
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• 2023

Traditional markets, formed naturally, often feature aged buildings and facilities that are susceptible to fire. However, the lack of adequate fire detection systems in these markets can easily lead to large-scale fires upon ignition. Therefore, this study was conducted with the aim of detecting fires in traditional markets, utilizing thermal imaging cameras for data collection and the YOLOv8 model for object detection experiments. Data were collected in the night markets within traditional markets of xx city and by simulating fire scenarios. A comparative analysis of the Nano and XL models of YOLOv8 revealed that the XL model is more effective in detecting fires. The XL model not only demonstrated higher accuracy in correctly identifying flames but also tended to miss fewer fires compared to the Nano model. In the case of objects other than flames, the XL model showed superior performance over the Nano model. Taking all these factors into account, it is anticipated that with further data collection and improvement in model performance, a suitable fire detection system for traditional markets can be developed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1352-1357
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• 2002

This Paper describes algorithm to extract license plates in vehicle images. Conventional methods perform preprocessing on the entire vehicle image to produce the edge image and binarize it. Hough transform is applied to the binary image to find horizontal and vertical lines, and the license plate area is extracted using the characteristics of license plates. Problems with this approach are that real-time processing is not feasible due to long processing time and that the license plate area is not extracted when lighting is irregular such as at night or when the plate boundary does not show up in the image. This research uses the gray level transition characteristics of license plates to verify the digit area by examining the digit width and the level difference between the background area the digit area, and then extracts the plate area by testing the distance between the verified digits. This research solves the problem of failure in extracting the license plates due to degraded plate boundary as in the conventional methods and resolves the problem of the time requirement by processing the real time such that practical application is possible. This paper Presents a power automated license plate recognition system, which is able to read license numbers of cars, even under circumstances, which are far from ideal. In a real-life test, the percentage of rejected plates wan 13%, whereas 0.4% of the plates were misclassified. Suggestions for further improvements are given.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.2
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• pp.113-125
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• 2012

This research is aimed at evaluating the land surface characterization of KOMPSAT-3A middle infrared (MIR) data. Airborne Hyperspectral Scanner (AHS) data, which has MIR bands with high spatial resolution, were used to assess land surface temperature (LST) retrieval and classification accuracy of MIR bands. Firstly, LST values for daytime and nighttime, which were calculated with AHS thermal infrared (TIR) bands, were compared to digital number of AHS MIR bands. The determination coefficient of AHS band 68 (center wavelength $4.64{\mu}m$) was over 0.74, and was higher than other MIR bands. Secondly, The land cover maps were generated by unsupervised classification methods using the AHS MIR bands. Each class of land cover maps for daytime, such as water, trees, green grass, roads, roofs, was distinguished well. But some classes of land cover maps for nighttime, such as trees versus green grass, roads versus roofs, were not separated. The image classification using the difference images between daytime AHS MIR bands and nighttime AHS MIR bands were conducted to enhance the discrimination ability of land surface for AHS MIR imagery. The classification accuracy of the land cover map for zone 1 and zone 2 was 67.5%, 64.3%, respectively. It was improved by 10% compared to land cover map of daytime AHS MIR bands and night AHS MIR bands. Consequently, new algorithm based on land surface characteristics is required for temperature retrieval of high resolution MIR imagery, and the difference images between daytime and nighttime was considered to enhance the ability of land surface characterization using high resolution MIR data.

• Journal of Bio-Environment Control
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• v.25 no.4
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• pp.302-307
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• 2016

The aim of this study was to examine the optimum wattage and installation height using nano-carbon fiber infrared heating lamp (NCFIHL) for heating energy saving and plug seedling production in plug seedling production greenhouse in winter season. NCFIHL of 700 and 900 W was installed over the bed ($1.2{\times}2.4m$) as 0.7, 1.0, and 1.3 m height, respectively, for the production of grafted watermelon seedling in venlo-type glasshouse. Watermelon (Citrullus lanatus (Thunb.) Manst.) 'Jijonggul' and gourd (Lagenaria leucantha Rusby.) 'Sunbongjang' were used as scions and rootstocks, respectively. The scions and rootstocks were grafted by single cotyledon ordinary splice grafting. Light intensity of NCFIHL was below the $1{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ in all treatment. Spectral distributions of NCFIHL presented mostly infrared area. When outside air temperature was below $10^{\circ}C$, 700 and 900 W NCFIHL installed with 0.7 m height treatment and 900 W NCFIHL installed with 1.0 m height treatment maintained the setting air temperature ($20^{\circ}C$) at night. In the result of taking thermal imaging, the grafted watermelons were getting warm fast in 900 W NCFIHL installed with 0.7 m height treatment at night. Compactness of the grafted watermelons was the greatest in 700 W NCFIHL installed with 1.3 m height treatment. The results indicate that NCFIHL installed above 1.0 m height using 700 W was suitable for production of plug seedling.

• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.104-109
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• 2010

The lighting reflection is a common problem in image analysis and causes the many difficulties to extract distinct features in related fields. Furthermore, the problem grows in the rainy night. In this paper, we aim to remove light reflection effects and reconstruct a road surface without lighting reflections in order to extract distinct features. The proposed method utilizes a 3D analysis based on a multiple geometry using captured images, with which we can combine each reflected areas; that is, we can remove lighting reflection effects and reconstruct the surface. At first, the regions of lighting sources and reflected surfaces are extracted by local maxima based on vertically projected intensity-histograms. After that, a fundamental matrix and homography matrix among multiple images are calculated by corresponding points in each image. Finally, we combine each surface by selecting minimum value among multiple images and replace it on a target image. The proposed method can reduces lighting reflection effects and the property on the surface is not lost. While the experimental results with collected data shows plausible performance comparing to the speed, reflection-overlapping areas which can not be reconstructed remain in the result. In order to solve this problem, a new reflection model needs to be constructed.

• The KIPS Transactions:PartB
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• v.18B no.3
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• pp.117-130
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• 2011

The purpose of this study is to produce a better way to detect crossroad accidents, which involves an efficient method to produce background images in consideration of object movement and preserve/demonstrate the candidate accident region. One of the prior studies proposed an employment of traffic signal interval within crossroad to detect accidents on crossroad, but it may cause a failure to detect unwanted accidents if any object is covered on an accident site. This study adopted inverse perspective mapping to control the scale of object, and proposed different ways such as producing robust background images enough to resist surrounding noise, generating candidate accident regions through information on object movement, and by using edge information to preserve and delete the candidate accident region. In order to measure the performance of proposed algorithm, a variety of traffic images were saved and used for experiment (e.g. recorded images on rush hours via DVR installed on crossroad, different accident images recorded in day and night rainy days, and recorded images including surrounding noise of lighting and shades). As a result, it was found that there were all 20 experiment cases of accident detected and actual effective rate of accident detection amounted to 76.9% on average. In addition, the image processing rate ranged from 10~14 frame/sec depending on the area of detection region. Thus, it is concluded that there will be no problem in real-time image processing.

• Korean Journal of Optics and Photonics
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• v.30 no.2
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• pp.37-47
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• 2019

A reflecting omnidirectional optical system with four spherical and aspherical mirrors, for use with long-wavelength infrared light (LWIR) for night surveillance, is proposed. It is designed to include a collecting pseudo-Cassegrain reflector and an imaging inverse pseudo-Cassegrain reflector, and the design process and performance analysis is reported in detail. The half-field of view (HFOV) and F-number of this optical system are $40-110^{\circ}$ and 1.56, respectively. To use the LWIR imaging, the size of the image must be similar to that of the microbolometer sensor for LWIR. As a result, the size of the image must be $5.9mm{\times}5.9mm$ if possible. The image size ratio for an HFOV range of $40^{\circ}$ to $110^{\circ}$ after optimizing the design is 48.86%. At a spatial frequency of 20 lp/mm when the HFOV is $110^{\circ}$, the modulation transfer function (MTF) for LWIR is 0.381. Additionally, the cumulative probability of tolerance for the LWIR at a spatial frequency of 20 lp/mm is 99.75%. As a result of athermalization analysis in the temperature range of $-32^{\circ}C$ to $+55^{\circ}C$, we find that the secondary mirror of the inverse pseudo-Cassegrain reflector can function as a compensator, to alleviate MTF degradation with rising temperature.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.283-298
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• 2022

As Synthetic Aperture Radar (SAR) image can be acquired regardless of the weather and day or night, it is highly recommended to be used for Automatic Target Recognition (ATR) in the fields of surveillance, reconnaissance, and national security. However, there are some limitations in terms of cost and operation to build various and vast amounts of target images for the SAR-ATR system. Recently, interest in the development of an ATR system based on simulated SAR images using a target model is increasing. Attributed Scattering Center (ASC) matching and template matching mainly used in SAR-ATR are applied to target classification. The method based on ASC matching was developed by World View Vector (WVV) feature reconstruction and Weighted Bipartite Graph Matching (WBGM). The template matching was carried out by calculating the correlation coefficient between two simulated images reconstructed with adjacent points to each other. For the performance analysis of the two proposed methods, the Synthetic and Measured Paired Labeled Experiment (SAMPLE) dataset was used, which has been recently published by the U.S. Defense Advanced Research Projects Agency (DARPA). We conducted experiments under standard operating conditions, partial target occlusion, and random occlusion. The performance of the ASC matching is generally superior to that of the template matching. Under the standard operating condition, the average recognition rate of the ASC matching is 85.1%, and the rate of the template matching is 74.4%. Also, the ASC matching has less performance variation across 10 targets. The ASC matching performed about 10% higher than the template matching according to the amount of target partial occlusion, and even with 60% random occlusion, the recognition rate was 73.4%.