• Journal of the Korean Society of Clothing and Textiles
• /
• v.24 no.1
• /
• pp.24-33
• /
• 2000

The purpose of this study was to investigate the characteristic and image of oriental costume design on represented among three countries, Korea, China and Japan. The specific objectives were; 1) to identify the design characteristics of oriental costume. 2) to investigate the hierarchic structure of oriental costume image and the meaning structure of oriental costume image. The stimulus were 75 costume design of contemporary costume which represented the traditional image of orient. The main survey of questionary consisted of their evaluation of the oriental costume image by 26 semantic differential bi-polar scales and the subjects were 99 female students majoring in clothing and textiles. The data were analyze by Cluster analysis. Factor analysis, ANOVA, Scheffe test. The major findings were as follows; 1) As a result of design analysis, costume design of Korea, China, Japan had differences on form, color, texture, pattern, ornament, etc. 2) The hierarchic structure of oriental costume image consisted of elegance, sexy, feminine. Through factor analysis about oriental costume image 7 factors were identified; Attention, Attractiveness, Sexiness, Activeness, Weightness, Classics, Classics, Maturity. It was found out strongly that Korean costume image was simple and comfort image, Chinese costume image was sexy and feminine image, Japanese costume image was luxurious and mature image.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.36 no.6
• /
• pp.594-599
• /
• 2008

Image data produced from ADD water-tunnel test are currently analyzed manually. The accuracy and elapsed time of this process can be determined by observers. In this paper, the algorithm based on MATLAB for improved image data processing and analysis is proposed. This algorithm consists of camera calibration, gray-level transformation, noise filtering and binarization in image preprocessing, vortex trajectory measurement in image analysis. Experimental results show that the proposed algorithm has better accuracy and execution speed than those of the existing methods.

• Journal of Fashion Business
• /
• v.21 no.3
• /
• pp.29-42
• /
• 2017

This study investigates the impact of female consumer self-image on pursued fashion style. A survey was carried out among 717 women between the ages of 20 and 60 living in Seoul, Incheon, and Gyeonggi. Analysis was conducted in the following manner: SPSS 18.0 was used to perform an Exploratory Factor Analysis (descriptive analysis, principal factor analysis, Pearson correlation analysis, frequency analysis, and reliability analysis) and AMOS 21.0 was used to carry out a Confirmatory Factor Analysis. Based on a Structure Equation Model, results show that ideal self-image and realistic self-image, which are factors derived from psychology, affect pursued fashion style. By contrast, social self-image - derived from social contexts - does not. Therefore, the female consumers' self-image influences pursued fashion style; this is opposed to the relationship between the realistic self-image and ideal self-image of women, which is more unconscious and self-satisfying. The presented results indicate that we should respond to changes in the fashion industry and develop a deeper understanding of consumer niches to discover the factors that predict purchasing behavior. This knowledge can then be applied to establish market strategies. This study contributes to the literature by producing preliminary data that can help support such strategy formulation in the fashion and clothing industry.

• Journal of Fashion Business
• /
• v.10 no.2
• /
• pp.60-82
• /
• 2006

The purpose of this study was to confirm and practical use the street fashion design analysis system(Web-SFAS) which was designed in preceding research. Web-SFAS was developed to analyze data fast, accurately, conveniently, and to provide them to related fields by using Information Technology (IT) in fashion design industry. By inputting, sorting and analyzing actual image data into this system, it purposes to check if it needs to be corrected and to verify its operation and application. For this study, 191 street fashion image and paper questionaries were collected on Oct. 16th from 4pm to 7pm in Gyeong-Nam area(4 markets), 2004. This study was processed basically cross research(real time research). The collected data and paper questionaries were analysed by 4 experts who had over Master Degrees, and the results were input to the Web-SFAS system. This system analyzed the results as follow ; First, Top is usually wear T-shirts, cardigan item of soft material, Bottom is usually wear Skirt, jean item of hard material. Second, As for shoes, pumps were the most popular, and as for accessories, diverse items such as shoulder bag, jewelry, and totebag were preferred. Third, fashion image, most people wear a sportive casual style with semi-casual in a close second. Therefore, We also expect that this data can be used a prediction for the next seasons design trends and needs, especially if we make an online database through this development system, then it will be easier to access faster and more accurate fashion information.

• Proceedings of the Korean Information Science Society Conference
• /
• 2002.10d
• /
• pp.301-303
• /
• 2002

Subspace analysis is a popular method for multivariate data analysis and is closely related to factor analysis and principal component analysis (PCA). In the context of image processing (especially positron emission tomography), all data points are nonnegative and it is expected that both basis images and factors are nonnegative in order to obtain reasonable result. In this paper We present a sequential EM algorithm for rectified subspace analysis (subspace in nonnegativity constraint) and apply it to dynamic PET image analysis. Experimental results show that our proposed method is useful in dynamic PET image analysis.

• Korean Journal of Remote Sensing
• /
• v.25 no.6
• /
• pp.517-529
• /
• 2009

Many satellite image fusion techniques have been developed in order to produce a high resolution multispectral (MS) image by combining a high resolution panchromatic (PAN) image and a low resolution MS image. Heretofore, most high resolution image fusion techniques have used IKONOS and QuickBird images. Recently, GeoEye-1, offering the highest resolution of any commercial imaging system, was launched. In this study, we have experimented with GeoEye-1 images in order to evaluate which fusion algorithms are suitable for these images. This paper presents compares and evaluates the efficiency of five image fusion techniques, the $\grave{a}$ trous algorithm based additive wavelet transformation (AWT) fusion techniques, the Principal Component analysis (PCA) fusion technique, Gram-Schmidt (GS) spectral sharpening, Pansharp, and the Smoothing Filter based Intensity Modulation (SFIM) fusion technique, for the fusion of a GeoEye-1 image. The results of the experiment show that the AWT fusion techniques maintain more spatial detail of the PAN image and spectral information of the MS image than other image fusion techniques. Also, the Pansharp technique maintains information of the original PAN and MS images as well as the AWT fusion technique.

• Journal of the Korean Data and Information Science Society
• /
• v.16 no.4
• /
• pp.879-888
• /
• 2005

Fashion is hard to expect owing to the rapid change in accordance with consumer taste and environment, and has a tendency toward variety and individuality. Especially street fashion of 21st century is not being regarded as one of the subcultures but is playing an important role as a fountainhead of fashion trend. Therefore, Searching and analyzing street fashions helps us to understand the popular fashions of the next season and also it is important in understanding the consumer fashion sense and commercial area. So, we need to understand fashion styles quantitatively and qualitatively by providing visual data and dividing images. There are many kinds of data in street fashion information. The purpose of this study is to design and implementation for street fashion information analysis system using data fusion. We can show visual information of customer's viewpoint because the system can analyze the fused data for image data and survey data.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.530-532
• /
• 2007

Multi-Spectral Camera(MSC) is a main payload on the KOMPSAT-2 satellite to perform the earth remote sensing. The MSC instrument has one(1) channel for panchromatic imaging and four(4) channel for multi-spectral imaging covering the spectral range from 450nm to 900nm using TDI CCD Focal Plane Array (FPA). The compression method on KOMPSAT-2 MSC was selected and used to match EOS input rate and PDTS output data rate on MSC image data chain. At once the MSC performance was carefully handled to minimize any degradation so that it was analyzed and restored in KGS(KOMPSAT Ground Station) during LEOP and Cal./Val.(Calibration and Validation) phase. In this paper, on-orbit image data chain in MSC and image data processing on KGS including general MSC description is briefly described. The influences on image performance between on-board compression algorithms and between performance restoration methods in ground station are analyzed and discussed.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.17 no.1
• /
• pp.3-10
• /
• 1993

This study intends to provide a beneficial foundation which can aid our understanding of how a clothing consumer group can be classified according to the clothing buying motives, and what differences are there about the importances store image attribute among them and how consumer's preferences to the store image are shown differently among them and ultimately, some concrete data which can be useful in establishing efficient store image strategies for clothing stores. 484 subjects were gathered through convenience sampling method and, for data analysis, cronbach' ${\alpha}$, frequency, percentage, mean, ${\chi}^2$-text, t-test, ANOVA, Duncan Multiple Range Test, Factor Analysis, Cluster Analysis were conducted. the results are as follows; 1. three kind of factors in the clothing buying motives were determined for analysis of consumers group and by which it was revealed as to be significant for us to classify them three subdivisions; those of fashion pursuit group, self display group, financial utilitarian group. 2. Importance on store image attribute was revealed that Ewha students regarded quality, price, more important factors than others. 3. Store image preferences show significantly when concerned with quality, price, fashion, impression and age of store personnel, convenience for exchanging and returning goods, credit, delivery and repair, mailing of catalogue and discount coupon, bightness of store among consumer groups.

• Journal of Korea Game Society
• /
• v.21 no.6
• /
• pp.75-86
• /
• 2021

Brand image refers to how customers, stakeholders and the market see and recognize the brand. A positive brand image leads to continuous purchases, but a negative brand image is directly linked to consumers' buying behavior, such as stopping purchases, so from the corporate perspective, it needs to be quickly and accurately identified. Currently, methods of investigating brand images include surveys and SNS surveys, which have limited number of samples and are time-consuming and costly. Therefore, in this study, we are going to conduct an emotional analysis of text data on social media by utilizing the machine learning based KoBERT model, and then suggest how to use it for game corporate brand image analysis and verify its performance. The result has proved some degree of usability showing the same ranking within five brands when compared with the BRI Korea's brand reputation ranking.