• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.105-114
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• 2006

In ubiquitous environment where various kinds of computers are embedded in persons, objects and environment and they are interconnected and can be used in my place as necessary, different types of data need to be exchanged between heterogeneous machines through home network. In the environment, the efficient processing, transmission and monitoring of image data are essential technologies. We need to make research not only on traditional image processing such as spatial and visual resolution, color expression and methods of measuring image quality but also on transmission rate on home network that has a limited bandwidth. The present study proposes a new motion vector estimation algorithm for transmitting, processing and controlling image data, which is the core part of contents in home network situation and, using algorithm, implements a real time monitoring system of multi dimensional images transmitted from multiple cameras. Image data of stereo cameras to be transmitted in different environment in angle, distance, etc. are preprocessed through reduction, magnification, shift or correction, and compressed and sent using the proposed metamorphosis hierarchical motion vector estimation algorithm for the correction of motion. The proposed algorithm adopts advantages and complements disadvantages of existing motion vector estimation algorithms such as whole range search, three stage search and hierarchical search, and estimates efficiently the motion of images with high variation of brightness using an atypical small size macro block. The proposed metamorphosis hierarchical motion vector estimation algorithm and implemented image systems can be utilized in various ways in ubiquitous environment.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.825-834
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• 2023

The demands of people who purchase fashion products on Internet shopping are gradually increasing, and attempts are being made to provide user-friendly images with 3D contents and web 3D software instead of pictures and videos of products provided. As a reason for this issue, which has emerged as the most important aspect in the fashion web shopping industry, complaints that the product is different when the product is received and the image at the time of purchase has been heightened. As a way to solve this problem, various image processing technologies have been introduced, but there is a limit to the quality of 2D images. In this study, we proposed an automatic conversion technology that converts 2D images into 3D and grafts them to web 3D technology that allows customers to identify products in various locations and reduces the cost and calculation time required for conversion. We developed a system that shoots a mannequin by placing it on a rotating turntable using only 8 cameras. In order to extract only the clothing part from the image taken by this system, markers are removed using U-net, and an algorithm that extracts only the clothing area by identifying the color feature information of the background area and mannequin area is proposed. Using this algorithm, the time taken to extract only the clothes area after taking an image is 2.25 seconds per image, and it takes a total of 144 seconds (2 minutes and 4 seconds) when taking 64 images of one piece of clothing. It can extract 3D objects with very good performance compared to the system.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.525-532
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• 2024

This study explores the impact of physical characteristics (e.g., shape, color, material, size, weight, technical features) of smart wristbands and smartwatches on consumers' perceived functional, aesthetic, and symbolic values using an extended technology acceptance model. An online survey was conducted with adult residents of the United States who had experience using smart wristbands or smartwatches. Participants were asked about various physical characteristics of products they had used in the past year or were currently using, and their evaluations of these characteristics. The results revealed that the shape of the front display shape significantly influenced symbolic value, with circle shape and square shpae showing significantly higher symbolic value than rectangle shape. Wristband materials also had a significant impact on symbolic value, with metal and leather showing higher symbolic value among various materials. Additionally, an increase in product size was associated with higher symbolic value. Moreover, certain technical features such as activity tracker, alarm clock, and distance tracking influenced perceived functional value, while functions like time display, GPS, and email influenced perceived aesthetic value. Pedometer, GPS, and email were found to enhance perceived symbolic value. These findings provide valuable insights into consumer preferences for smart wristbands and smartwatches, serving as valuable information for product improvement and new product development.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.39 no.2
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• pp.117-125
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• 2013

In this study, The stability of a cream containing the ethyl acetate fraction of 50% ethanol extracts from Glycyrrhiza uralensis (G. uralensis) cultured in Korea was investigated. pH, absorbance, viscosity and color difference of the cream containing 0.20% ethyl acetate fraction of the aforementioned G. uralensis extracts were measured under 4 different temperature conditions ($4^{\circ}C$ $25^{\circ}C$ $37^{\circ}C$ and $45^{\circ}C$) and under the sun light at 2 week intervals for 12 weeks. pH changes of a control cream without the extracts and the sample cream containing 0.20% ethyl acetate fraction of G. uralensis extracts were 0.66 and 0.44, respectively. There were no significant pH differences between the sample and the control under the sun. Viscosities of the control cream and the sample cream decreased by 2,483 cPs and 2,893 cPs respectively. So, the sample cream showed a bigger decline (410 cP) in viscosity than the control cream. The ethyl acetate fraction of G. uralensis extracts did not affect the stability of the cream. Absorbance of ethanol solution of the ethyl acetate fraction decreased 30.00% at 276 nm under the sun. On the other hand, the absorbance of the sample cream containing the ethyl acetate fraction decreased 12.02%. The stability of the G. uralensis extracts was better in cream formulation than in ethanol solution. The total color differences of all creams increased slightly during the study period under various conditions. The results appeared to indicate the color stability of the cream containing 0.20% ethyl acetate fraction of G. uralensis extracts. It is suggested that further study is needed to provide more information to the manufacturers who are seeking for the application of the G. uralensis extracts to improve the anti-oxidant and stability of cosmetic products.

• Journal of the Korean earth science society
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• v.32 no.7
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• pp.809-831
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• 2011

Sea Surface Temperature (SST) is one of the most important oceanic variables to understand rapidly-changing climate, so that accurate and error-free SST images should be presented in school science textbooks. However, satelliteobserved SST images in the high-school textbooks presented some errors caused by various reasons. This study analyzed 36 satellite images for SST presented in 24 kinds of high-school textbooks (earth science I and II textbooks on the basis of the 7th National Curriculum) for 17 items. This study investigated errors in image processing such as cloud removal, land masking, color bar, geological and time information, and some erroneous expressions related to the fundamental information of satellites. Twenty five pre-service teachers filled out a survey about several problematic satellite images, and their responses were analyzed. As a result, most of the pre-service teachers did not recognize the errors associated with image processing and tended to comprehend the SST errors as real oceanographic phenomena such as sea ice, river outflow, or cold current. Therefore, satellite SST images in the textbooks should be accurately presented by including detailed items suggested in this study.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.3
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• pp.11-22
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• 2010

This paper is a study on implementation of intelligent image surveillance system using context information and supplements temporal-spatial constraint, the weak point in which it is hard to process it in real time. In this paper, we propose scene analysis algorithm which can be processed in real time in various environments at low resolution video(320*240) comprised of 30 frames per second. The proposed algorithm gets rid of background and meaningless frame among continuous frames. And, this paper uses wavelet transform and edge histogram to detect shot boundary. Next, representative key-frame in shot boundary is selected by key-frame selection parameter and edge histogram, mathematical morphology are used to detect only motion region. We define each four basic contexts in accordance with angles of feature points by applying vertical and horizontal ratio for the motion region of detected object. These are standing, laying, seating and walking. Finally, we carry out scene analysis by defining simple context model composed with general context and emergency context through estimating each context's connection status and configure a system in order to check real time processing possibility. The proposed system shows the performance of 92.5% in terms of recognition rate for a video of low resolution and processing speed is 0.74 second in average per frame, so that we can check real time processing is possible.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.2
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• pp.141-147
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• 2015

The contrast of a display is generally evaluated by using the ratio of the minimum luminance to the maximum luminance of the display. However, this contrast ratio is not matched with perceived contrast because it uses only physical characteristic of display without considering human perceptual characteristics. In this paper, the proposed contrast measure that considers perceptually discriminable brightness within the range of display brightness is suggested. First, the range between the minimum and maximum brightness of display in CIECAM02 color space is calculated to measure the length of perceived brightness for the display. Next, brightness ranges which are perceptually same at each brightness level are determined by applying Weber-Fechner ratio and then, the number of brightness values within each brightness range is counted. Finally, perceptually discriminable brightness is defined as the sum of ratio between the number of brightness values in each brightness range and the perceptual contrast length of the display. In the experiments, preference test using various displays with random brightness patches is performed to evaluate perceived contrast. As a result, the proposed measure is more consistent with human perception than the previous contrast measures.

• Journal of the Korea Computer Graphics Society
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• v.24 no.1
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• pp.9-16
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• 2018

In this paper, we introduce a visualization framework for cell image data obtained from optical diffraction tomography (ODT), including a method for representing cell morphology in 3D virtual environment and a color mapping protocol. Unlike commonly known volume data sets, such as CT images of human organ or industrial machinery, that have solid structural information, the cell image data have rather vague information with much morphological variations on the boundaries. Therefore, it is difficult to come up with consistent representation of cell structure for visualization results. To obtain desired visual representation of cellular structures, we propose an interactive visualization technique for the ODT data. In visualization of 3D shape of the cell, we adopt a volume rendering technique which is generally applied to volume data visualization and improve the quality of volume rendering result by using empty space jittering method. Furthermore, we provide a layer-based independent rendering method for multiple transfer functions to represent two or more cellular structures in unified render window. In the experiment, we examined effectiveness of proposed method by visualizing various type of the cell obtained from the microscope which can capture ODT image and fluorescence image together.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.129-136
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• 2014

This study deals with red tide detection by using the remote sensing imagery from the Geostationary Ocean Color Imager (GOCI), the world's first geostationary orbit satellite, around the southern coast of Korea where the most severe red tide occurred recently. The red tide zone was determined by the available data selection from the GOCI imagery during the period of red tide occurrence and also the severe red tide zone was detected through the spatial analysis by temporal change out of the red tide zone. This study results showed that the coast in the vicinity of the Hansan and Yokji in Tongyeong-si was classified into the severe red tide zone, and that the red tide was likely to spread from the coast of Hansan and Yokji to the one of Sanyang-eub. In addition, the comparative analysis between the area of red tide occurrence, the prevention activities of Gyeongsangnam-do provincial government and the amount of the damage cost over time showed close correlation among them. It is still early to conclude that the study is showing the severe red tide zone and the spread path exactly due to various factors for red tide occurrence and activities. In order to improve the reliability of the results, the more data analysis is required.