• Korean Institute of Interior Design Journal
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• v.21 no.3
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• pp.111-118
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• 2012

The purpose of this study is to focus on living rooms that are preferred as a place for changing space image to the maximum and to find a method how finishing materials are expressed by selecting space with mix & match of many images. The study methods are as follows. First, understand the expressive trend of space images through the precedent studies and magazines, and examine its relationship with finishing materials. Second, select space images based on the contents understood earlier and extract adjective words that represent each space image through an expert survey. Third, find the cases where space images are expressed based on the extracted words and analyze expression methods of finishing materials. The results of the study are as follows. First, it was confirmed that recent space images are actively expressed through finishing materials. Second, space images selected through data related to the trend were classified as modern+natural, modern+traditional, modern+retro, classic+natural, classic+humor, and futurism+natural and 4 adjective words for each space image were extracted. Third, expressive elements of finishing materials were extracted as 'material'. 'texture', 'color', and 'pattern' through the precedent studies. Fourth, expressive methods of finishing materials for each space image could be suggested by analyzing the examples that show mix & match based on the contents extracted earlier. Lastly, it is expected to find various methods that lead space image into finishing materials by evaluating responses and changes in visual perception of residents according to expression of finishing materials based on this study.

• Human Ecology Research
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• v.52 no.1
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• pp.21-31
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• 2014

The purpose of this study was to analyze the types and meanings of calligraphy presented in modern fashion design. Calligraphy refers to beautiful handwriting or fine penmanship in the West, and handwriting with brushstrokes in the East. The expression patterns being used at present can be divided into three categories. Legible calligraphy is focused on readability more than embellishment. Decorative calligraphy places its importance on decoration at the expense of practicality. The third type, harmonious calligraphy, pursues decorativeness and legibility at the same time. Each of these types of calligraphy is expressed in modern fashion with its own purpose: calligraphy for conveying emotional messages, calligraphy as a special brand image, and calligraphy as an expression of formativeness. The first, calligraphy for conveying emotional messages, is used with characters that are familiar to the public. Calligraphy of this type delivers messages confined emotionally to the conscious world, harmonizing calligraphy with words, or expressing readability filled with purity and delight. Second, calligraphy as a special brand image refers to transmitting a distinctive brand image from other companies through employment of a design motive or pattern by expressing the brand logos or names of designers. Third, calligraphy as a expression of formativeness has the function of shaping expressions as motives or patterns, avoiding meanings of words or phrases. It can be represented by the abbreviation or modification of words, or arranging words in different shapes, harmonizing the words with the clothing construction and atmosphere of the other images.

• Science of Emotion and Sensibility
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• v.6 no.3
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• pp.45-54
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• 2003

This study is designed to extract sensibility words of mobile phone image and analyze the relational patterns among those words to develope a sensibility model for mobile phone design. We expected the different sensibility scale would be developed according to the case of open or closed. The 25 representative words were abstracted as a result of words collection. As a result of the factor analysis of sensibility evaluation for mobile phone, the mobile phone design image was different according to the state of folding and unfolding. In the state of folder unfolding, the first factor was named as 'cool', the second factor as 'soft' and the third factor as 'handy'. In the state of folding, the first factor was named as 'stylish', the second factor as 'variegated' and the third factor as 'hard'.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.369-378
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• 2005

Document image is segmented and classified into text, picture, or table by a document layout analysis, and the words in table regions are significant for keyword spotting because they are more meaningful than the words in other regions. This paper proposes a method to extract words from table regions in document images. As word extraction from table regions is practically regarded extracting words from cell regions composing the table, it is necessary to extract the cell correctly. In the cell extraction module, table frame is extracted first by analyzing connected components, and then the intersection points are extracted from the table frame. We modify the false intersections using the correlation between the neighboring intersections, and extract the cells using the information of intersections. Text regions in the individual cells are located by using the connected components information that was obtained during the cell extraction module, and they are segmented into text lines by using projection profiles. Finally we divide the segmented lines into words using gap clustering and special symbol detection. The experiment performed on In table images that are extracted from Korean documents, and shows $99.16\%$ accuracy of word extraction.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.591-598
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• 2021

It's possible to get the word-vector by the statistical SVD or deep-learning CBOW and LSTM methods and theses ones learn the contexts of forward/backward words or the sequence of following words. It's used to analyze the poems by Ki Hyung-do with similar words recommended by the word-vector showing the core images of the poetry. It seems at first sight that the words don't go well with the images but they express the similar style described by the reference words once you look close the contexts of the specific poems. The word-vector can analogize the words having the same relations with the ones between the representative words for the core images of the poems. Therefore you can analyze the poems in depth and in variety with the similarity and analogy operations by the word-vector estimated with the statistical SVD or deep-learning CBOW and LSTM methods.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1125-1133
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• 2014

Recently, there are many researches have been studying for analyzing user interests and emotions based on users profiles and diverse information from Social Network Services (SNSs) due to their popularities. However, most of traditional researches are focusing on their researches based on single resource such as text, image, hash tag, and more, in order to obtain what user emotions are. Hence, this paper propose a method for obtaining user emotional information by analyzing texts and images both from Instagram which is one of the well-known image based SNSs. In order to extract emotional information from given images, we firstly apply GRAB-CUT algorithm to retrieve objects from given images. These retrieved objects will be regenerated by their representative colors, and compared with emotional vocabulary table for extracting which vocabularies are the most appropriate for the given images. Afterward, we will extract emotional vocabularies from text information in the comments for the given images, based on frequencies of adjective words. Finally, we will measure WUP similarities between adjective words and emotional words which extracted from the previous step. We believe that it is possible to obtain more precise user emotional information if we analyzed images and texts both time.

• Journal of the Korea Fashion and Costume Design Association
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• v.14 no.2
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• pp.147-156
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• 2012

The purpose of this study is to analyze the style of wide pants shown in collections from 2008 to 2011 and to extract main expressional words for the development of semantic differential scales of visual images according to the change in silhouette of wide pants. The results of this study are as follows: 1) The wide pants which women wore in the 1970s were similar to men's. The aesthetic values for the wide pants included the social women's requests of the time. On the other hand, new wide pants shown in the current collections have diversified by adding designers' will to express contemporary women's tastes and fashion senses. 2) 742 wide pants shown in collections were composed of 459 straight, 147 bell-bottom and 136 flared pants. The design differs according to changes in the waist position and width of the wide pants. 3) Main expressional words of visual images for wide pants differ greatly depending on the silhouette of wide pants. The visual images are ranked in the order of 'showed that legs are long', 'looked taller', 'neat', 'relaxed', 'retro', 'modern' for straight pants. The words of 'retro', 'countrified', 'legs seemed to be long', 'enough' 'confident' 'looked like thighs that are slim' are ranked for bell-bottom pants. And the words of 'plentiful' 'loose', 'enough', 'retro' 'uncomfortable', 'relaxed', 'countrified' are marked down for flared pants.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.97-118
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• 2011

The study examines the interactive effect of spoken words and imagery not synchronized in audio/image surrogates for video gisting. To do that, we conducted an experiment with 64 participants, under the assumption that participants would better understand the content of videos when viewing audio/image surrogates rather than audio or image surrogates. The results of the experiment showed that overall audio/image surrogates were better than audio or image surrogates for video gisting, although the unsynchronized multimedia surrogates made it difficult for some participants to pay attention to both audio and image when the content they present is very different.

• Fashion & Textile Research Journal
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• v.16 no.6
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• pp.995-1000
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• 2014

This study, using the free language association method, examined the characteristics of emotional words of respondents who were exposed to facial photos of women in 60s, and favorableness and favorable styles of them. To analyze mood characteristics on the faces, they were divided into positive mood words and negative mood words. Following previous researches, they were divided into introversion, extraversion, and ambiversion. It was found that the proportion of positive emotional words respondents used was 37%, and that of negative ones was 63%, demonstrating that respondents are more likely than not to get the negative impressions from the faces of their contemporaries. The characteristics of the words consists of 38% introversion, 47% extraversion, and 14% ambiversion. And, respondents used the words like 'beautiful' and 'good-looking' to the stimuli to which they felt favorable, and 'ill-tempered' and 'stubborn' to the stimuli to which they felt unfavorable. Third, the most favorable style to both male and female respondents in 60s were sentimental and good-mannered. They generally favor women who are soft and caring, and dislike talkative, snobbish, and thick make-up women. The analysis results in this paper may help image making and personal relations. Further study needs to expand the survey area to ensure more significant influence on the social life and interpersonal relationship of senior citizens.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2154-2168
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• 2022

Our work addresses the issues associated with usage of the semantic features by Bag of Words model, which requires construction of the dictionary. Extracting the relevant features and clustering them into code book or dictionary is computationally intensive and requires large storage area. Hence we propose to use a simple distribution of multiple shape based features, which is a mixture of gradients, radius and slope angles requiring very less computational cost and storage requirements but can serve as an equivalent image representative. The experimental work conducted on PASCAL VOC 2007 dataset exhibits marginally closer performance in terms of accuracy with the Bag of Word model using Self Organizing Map for clustering and very significant computational gain.