• Fashion & Textile Research Journal
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• v.14 no.3
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• pp.465-471
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• 2012

This thesis collected words, feelings, and psychological images expressed in female faces in their 20s and 60s. The comparative analysis of the characteristics will be based on the effective image of direction and improvement. Through the analyzed station of word of images collected, female faces in 20s of image are positive images such as pretty, cute, and elegant; however, there were also negative images such as gloomy, sharp, and stubborn. Female faces in 60s image are negative image such as scary, gloomy, sharp, and stubborn. To the analyzed station of word's tendency (usually expressed appearance), external-oriented tendency significantly developed in their 20s and 60s. It shows that the importance of appearance is emphasized in women face image in 20s and 60s.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.5
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• pp.748-759
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• 2000

The purposes of this study were 1) to classify wearing situation of male adolescents and 2) to classify self-image and CPI(Clothing Preference Image) of male adolescents and 3) to segment consumer group by self-image and to find the differences in self-image and CPI by situation among groups. For the data collection a questionnaire was distributed to male adolescents who were residents in Seoul and Taejeon. The statistics used for the data analysis were factor analysis, multiple dimensional scale, mean, percentage, peason-correlation, cluster analysis, one-way ANOVA, Duncan-test by the SPSSWIN program. The results of this study are as follows: 1) The self-image of male adolecents is categorized by seven factors; sophisticate and fashion conscious, active, practical and realistic, flank and pure, young-looking, feminine, and slender. Based on seven factors, the consumer group is categorized to five groups; practical and realistic Group1, young-looking and feminine Group2, characterless Group3, active Group4, sophisticate and flank Group5. 2) Wearing situations are divided into three categories; in downtown, in urban, at festival. In downtown, CPI are divided into six elements; ornamental, simplex, sexy, feminine, neat, young, and sophisticate. In urban, CPI are divided into five elements; ornamental, simple, sexy, feminine, young-looking, and sophisticate. At festival, CPI are divided into four elements; unique, simple, feminine, and formal. To conclude, the male adolescent consumers are categorized by self-image, and the different CPIs are sought by different wearing situations.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.259-268
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• 2019

This study examines the color image of uniform of airline cabin crew according to the demographic characteristics of the customer and demonstrates how it affects the cognitive image of airlines. Adjective adjectives were derived for uniform color images of all eight airlines in Korea and analyzed the image of airline brand color. Based on the analysis of color images, the difference in perception according to the demographic characteristics of passengers was analyzed. When the colors of airline uniforms are mainly blue, sky blue, white and ivory, they have a lot of trust, neat and elegant images. Uniforms with primary colors such as red, orange and green beans are found to have a lot of cheerful, developmental and enterprising images. In addition, the empirical analysis of the impact of the customer's cognitive perception and favoritism on the uniform color image of the airline crew showed that the more positive the airline's positive perception of the uniform color image, the more positive the cognitive image is. In other words, the empirical analysis revealed that the airline's uniform color image, its cognitive image of the airline, and its popularity have significant positive relationships.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.4
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• pp.313-332
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• 2014

With the increased creation, distribution, and use of image in context of the development of digital technologies and internet, research endeavors have accumulated drastically. As two dominant aspects of image retrieval have been considered content-based and concept-based image retrieval, concept-based image retrieval has been focused in the field of Library and Information Science. This study aims to systematically review the accumulated research of image retrieval from the perspective of LIS field. In order to achieve the purpose of this study, two data sets were prepared: a total of 282 image retrieval research papers from Web of Science, and a total of 35 image retrieval research from DBpia in Kore for comparison. For data analysis, systematic review methodology was utilized with bibliographic analysis of individual research papers in the data sets. The findings of this study demonstrated that two sub-areas, image indexing and description and image needs and image behavior, were dominant. Among these sub-areas, the results indicated that there were emerging areas such as collective indexing, image retrieval in terms of multi-language and multi-culture environments, and affective indexing and use. For the user-centered image retrieval research, college and graduate students were found prominent user groups for research while specific user groups such as medical/health related users, artists, and museum users were found considerably. With the comparison with the distribution of sub-areas of image retrieval research in Korea, considerable similarities were found. The findings of this study expect to guide research directions and agenda for future.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.5
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• pp.462-475
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• 2022

Different from the field of electro-optical(EO) image analysis, there has been less interest in similarity metrics between synthetic aperture radar(SAR) target images. A reliable and objective similarity analysis for SAR target images is expected to enable the verification of the SAR measurement process or provide the guidelines of target CAD modeling that can be used for simulating realistic SAR target images. For this purpose, this paper presents a similarity analysis method based on the siamese network that quantifies the subjective assessment through the distance learning of similar and dissimilar SAR target image pairs. The proposed method is applied to MSTAR SAR target images of slightly different depression angles and the resultant metrics are compared and analyzed with qualitative evaluation. Since the image similarity is somewhat related to recognition performance, the capacity of the proposed method for target recognition is further checked experimentally with the confusion matrix.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.5
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• pp.311-317
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• 2015

The aim of this study is to develop a 3D registration algorithm for positron emission tomography/computed tomography (PET/CT) and magnetic resonance (MR) images acquired from independent PET/CT and MR imaging systems. Combined PET/CT images provide anatomic and functional information, and MR images have high resolution for soft tissue. With the registration technique, the strengths of each modality image can be combined to achieve higher performance in diagnosis and radiotherapy planning. The proposed method consists of two stages: normalized mutual information (NMI)-based global matching and independent component analysis (ICA)-based refinement. In global matching, the field of view of the CT and MR images are adjusted to the same size in the preprocessing step. Then, the target image is geometrically transformed, and the similarities between the two images are measured with NMI. The optimization step updates the transformation parameters to efficiently find the best matched parameter set. In the refinement stage, ICA planes from the windowed image slices are extracted and the similarity between the images is measured to determine the transformation parameters of the control points. B-spline. based freeform deformation is performed for the geometric transformation. The results show good agreement between PET/CT and MR images.

• Journal of the Korea Fashion and Costume Design Association
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• v.18 no.3
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• pp.85-98
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• 2016

The purpose of this study was to investigate the adolescents' images and preference on cultural products based on Baekje traditional culture focused on adolescents. The subjects were 421 adolescents in Daejeon and Chungnam province. The measuring instruments was stimuli of cultural products and a questionnaire with semantic differential scales of image of cultural products, preference, product evaluation criteria, and subjects' demographics characteristics. The data were analyzed by Cronbach's ${\alpha}$, factor analysis, t-test, ANOVA, Duncan's multiple range test, and regression analysis using SPSS program. The results were as follows. First, 3 factors(attractiveness, interest, gentleness) were emerged on images of cultural products based on Baekje tradition culture, however, the current products could not convey affectively the attractive and gentle image of baekje traditional culture. Second, the preference of the Baekje cultural products was evaluated low, and especially design and price was rated low in the evaluation criteria. Third, preference was related with the 3 image factors, and attractiveness factor was showed highly positive effects on preference of cultural products. The implication of this study was to provide the useful cultural product development plan for adolescents, and the research results suggested that modern and individual design, unique traditional pattern, resonable price, and practicality have to be considered to develop successful cultural products for adolescents.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.33-36
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• 2003

Principal component analysis (PCA) was used to improve image classification by the unsupervised classification techniques, the K-means. To do this, I selected a Landsat TM scene of Jeju Island, Korea and proposed two methods for PCA： unstandardized PCA (UPCA) and standardized PCA (SPCA). The estimated accuracy of the image classification of Jeju area was computed by error matrix. The error matrix was derived from three unsupervised classification methods. Error matrices indicated that classifications done on the first three principal components for UPCA and SPCA of the scene were more accurate than those done on the seven bands of TM data and that also the results of UPCA and SPCA were better than those of the raw Landsat TM data. The classification of TM data by the K-means algorithm was particularly poor at distinguishing different land covers on the island. From the classification results, we also found that the principal component based classifications had characteristics independent of the unsupervised techniques (numerical algorithms) while the TM data based classifications were very dependent upon the techniques. This means that PCA data has uniform characteristics for image classification that are less affected by choice of classification scheme. In the results, we also found that UPCA results are better than SPCA since UPCA has wider range of digital number of an image.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.6
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• pp.585-592
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• 2015

In this study, by applying mobile based GIS and image analysis of particulate matter ($PM_{10}$) concentration in Seoul and Ulsan in Korea, to identify the user's location and also implemented the application to information exchange. It strengthened citizens' access to air quality information through the application and derived the expanded environment information sharing through real-time user participation. Through atmospheric concentrations image analysis, it showed a new environmental information construction possibility. It had the effect of expanding the information collecting through the local user participation on the limited information collected area which place is not yet constructed atmospheric monitoring network. Location-based particulate matter information service application provides a user location's $PM_{10}$ information from the 25 urban air monitoring network real-time database of the Ministry of Environment. Furthermore, if the user sent a picture of the atmosphere to the server, should match the image density values of the database and express on Seoul's maps through the IDW interpolation. And then a $PM_{10}$ concentration result is transmitted to user in real time.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.727-731
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• 2003

ASTER image has some advantages for classification such as 15 spectral bands and 15m ${\sim}$ 90m spatial resolution. However, in the classification using general remote sensing image, shadow areas are often classified into water area. It is very difficult to divide shadow and water. Because reflectance characteristics of water is similar to characteristics of shadow. Many land cover items are consisted in one pixel which is 15m spatial resolution. Nowadays, very high resolution satellite image (IKONOS, Quick Bird) and Digital Surface Model (DSM) by air borne laser scanner can also be used. In this study, mixed pixel analysis of ASTER image has carried out using IKONOS image and DSM. For mixed pixel analysis, high accurated geometric correction was required. Image matching method was applied for generating GCP datasets. IKONOS image was rectified by affine transform. After that, one pixel in ASTER image should be compared with corresponded 15×15 pixel in IKONOS image. Then, training dataset were generated for mixed pixel analysis using visual interpretation of IKONOS image. Finally, classification will be carried out based on Linear Mixture Model. Shadow extraction might be succeeded by the classification. The extracted shadow area was validated using shadow image which generated from 1m${\sim}$2m spatial resolution DSM. The result showed 17.2% error was occurred in mixed pixel. It might be limitation of ASTER image for shadow extraction because of 8bit quantization data.