• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.967-977
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• 2022

The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO₂), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.6
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• pp.463-470
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• 2022

Intravenous injection is widely used for patient treatment, including injection drugs, fluids, parenteral nutrition, and blood products, and is the most frequently performed invasive treatment for inpatients, including blood collection, peripheral catheter insertion, and other IV therapy, and more than 1 billion cases per year. Intravenous injection is one of the difficult procedures performed only by experienced nurses who have been trained in intravenous injection, and failure can lead to thrombosis and hematoma or nerve damage to the vein. Nurses who frequently perform intravenous injections may also make mistakes because it is not easy to detect veins due to factors such as obesity, skin color, and age. Accordingly, studies on auxiliary equipment capable of visualizing the venous structure of the back of the hand or arm have been published to reduce mistakes during intravenous injection. This paper is about the development of venous detection equipment that visualizes venous structure during intravenous injection, and the optimal combination was selected by comparing the brightness of acquired images according to the combination of near-infrared (NIR) LED and Filter with different wavelength bands. In addition, an image processing algorithm was derived to threshehold and making blood vessel part to green through grayscale conversion, histogram equilzation, and sharpening filters for clarity of vein images obtained through the implemented venous detection experimental module.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.105-112
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• 2023

In this paper, we propose a new method for displaying colored defects by measuring the relative density with the wide-area and local densities of X-ray. The relative density of one pixel represents a relative difference from the surrounding pixels, and we also suggest a colorization of X-ray images representing these pixels as normal and defective. The traditional method mainly inspects materials such as plastics and metals, which have large differences in transmittance to the object. Our proposed method can be used to detect defects such as sprouts or holes in images obtained by an inspection machine that detects X-rays. In the experiment, the products that could not be seen with the naked eye were colored with pests or sprouts in a specific color so that they could be used in the agricultural product selection system. Products that are uniformly filled with a single ingredient inside, such as potatoes, carrots, and apples, can be detected effectively. However, it does not work well with bumpy products, such as peppers and paprika. The advantage of this method is that, unlike machine learning, it doesn't require large amounts of data. The proposed method could be applied to a screening system using X-rays and used not only in agricultural product screening systems but also in manufacturing processes such as processed food and parts manufacturing, so that it can be actively used to select defective products.

• Korean Journal of Cognitive Science
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• v.16 no.4
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• pp.305-322
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• 2005

Watermarking is a widely employed method tn protecting copyright of a digital image, the owner's unique image is embedded into the original image. Strengthened level of watermark insertion would help enhance its resilience in the process of extraction even from various distortions of transformation on the image size or resolution. However, its level, at the same time, should be moderated enough not to reach human visibility. Finding a balance between these two is crucial in watermarking. For the algorithm for watermarking, the predefined strength of a watermark, computed from the physical difference between the original and embedded images, is applied to all images uniformal. The mean brightness or contrast of the surrounding images, other than the absolute brightness of an object, could affect human sensitivity for object detection. In the present study, we examined whether the detectability for watermark noise might be attired by image statistics: mean brightness and contrast of the image. As the first step to examine their effect, we made rune fundamental images with varied brightness and control of the original image. For each fundamental image, detectability for watermark noise was measured. The results showed that the strength ot watermark node for detection increased as tile brightness and contrast of the fundamental image were increased. We have fitted the data to a regression line which can be used to estimate the strength of watermark of a given image with a certain brightness and contrast. Although we need to take other required factors into consideration in directly applying this formula to actual watermarking algorithm, an adaptive watermarking algorithm could be built on this formula with image statistics, such as brightness and contrast.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.363-373
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• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.

• Journal of Information Display
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• v.2 no.3
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• pp.48-53
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• 2001

Carbon nanotube emitters, prepared by screen printing, have demonstrated a great potential towards low-cost, largearea field emission displays. Carbon nanotube paste, essential to the screen printing technology, was formulated to exhibit low threshold electric fields as well as an emission uniformity over a large area. Two different types of triode structures, normal gate and undergate, have been investigated, leading us to the optimal structure designing. These carbon nanotube FEDs demonstrated color separation and high brightness over 300 $cd/m^2$ at a video-speed operation of moving images. Our recent developments are discussed in details.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.189-197
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• 2009

A digital image usually has 8 bits of depth basically representing pixel intensity ranging for [0 255]. These pixel range allow 256 step levels of pixel values in the image. Thus the greyscale value for a given image is an integer. When we carry out interpolation of a given image for resizing we have to round the interpolated value to integer which can result in loss of quality on perceived color values. This paper proposes a new method for recovering this loss of information during interpolation process. By using the proposed method the pixels tend to regain more original values which yields better looking images on resizing.

• Journal of Fashion Business
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• v.14 no.2
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• pp.14-26
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• 2010

This study aims to investigate how the woman's beauty makeup trend had been changed in 1960s by analyzing the characteristics of woman's make-up in that period. For this study, a lot of documents and papers related to the woman's make-up were collected and reviewed. In particular, to analyze the characteristics of woman's make up trend in 1960s, a lot of women's pictures and makeup-related articles from 143 volumes of woman's magazines such as Yeowon and Jubusaenghwal were collected. Among the 624 pictures, fifty two pictures which were good enough for studying the total face and makeup were used for this study. The period of this study ranges from 1960 through 1969 and the analysis is focused on skin expression, eyebrow, eye shadow, eye line, lipstick, and brusher and through the related articles, the intention and contents of make up. were delivered and found out. The results are as follows. In early 1960s, the woman's make up was characterized by the make up ranging from unnatural and gray skin expression to dense pink skin expression, giving natural and glossy tint onto the skin and in particular putting a bright accent on the eyelid, eye or lip. In the mid-1960s, the make up style expressed skin more naturally, giving more shading on the eyelid, nose and lip, thus having cubic make-up. In the late 1960s, the make up became more refined and harmonized by using colors according to the TPO (time, place and objective) and skin color. The study results show that the women in 1960s pursued the "cute and young looking image" and used the make up to express their images young and cute. In the mid 1960s, the minimalism which pursued the pure and simple make up appeared in US. That trend affected the make up style of Korean women and hence Korean women showed more natural make up style in the mid and late 1960s.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.10
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• pp.1522-1534
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• 2008

The subjects of ttis study were middle-aged women in their 40s$\sim$50s and older women aged 60 and over who were living in Seoul and Kyonggi-do, Korea. Through studying the participants' responses to the questions regarding the attributes of image preference in terms of the levels of satisfaction and importance, the target consumers' demand has been studied. And, they are applied to a QFD Matrix, to find out the relationship between the attributes of product quality and the guidelines of clothing design. For this study, clothing image preference is categorized as three types: fashionable and urbane image, elegant and formal image, comfortable and active image. It has also been found that middle-aged and older women think the clothing that projects fashionable and urbane image needs more improvement that those for other images. To review demands for the clothing image preference attribute of formal suits for middle-aged and older women, the priority of these attributes through QFD Matrix that shows the relationship between the attributes and dress elements emphasized by designers has been examined. In reflecting clothing image preference by consumers for their formal two-piece suits, the most important design elements related to material in order of importance were material type, style, thickness and texture, and those related to color were the number of colors used and coloring type.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.107-115
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• 2014

Visibility of the road influence the safe driving because it recognizes the obstacle on the road. In this paper, we propose a mobile data acquisition and processing system for evaluating road visibility at night. And it was converted efficiently with mobile images and archived for spatial analysis of road-visibilities at night. This was applied to the following techniques to the system. Low-power computing units, open an image processing library, GPU-based acceleration techniques and document database techniques, etc. And converting the RGB image to the YUV color system, which was integrated the brightness component and the spatial information. High performance Android devices were used to collect brightness data on roads and it was confirmed whether this prototype was to determine the spatial distribution of such acquisition and management systems for spatial-assessments of road visibility at night.