• Title/Summary/Keyword: Classified Image

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A Study on the Characteristic Analysis of Housing Complex planning by Regional Characteristic (지역성을 고려한 주거단지계획의 특성분석을 위한 사래연구 -대구광역시 'U 대회 선수촌 단지'를 중심으로 -)

  • Seo Ji-Eun;Park Eui-Jeong
    • Journal of the Korean housing association
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    • v.17 no.3
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    • pp.31-40
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    • 2006
  • The purpose of this study is to grasp the present state of a outdoor space planning and to analysis plan characteristics in based on regional characteristics in Housing complex plan. The analysis result of this study is as follows : first, we know that the right of regional characteristics is appearing variously every research workers. also an analysis about regional characteristics that should be considered in housing complex plan was insufficient. Second, regional characteristics can be classified into 5 factors. These are classified as a context of location, city link, life atmosphere, needs of locals and creation of image. Third, it has originality against other housing complex to graft items connected with 'U contest' on outdoor space planning. Also, it has affirmatively effected on image of Buk-gu and recognition of Dong beyn-dong and Seo beyn-dong. It is get out of the uniform design by a planning based on land and surrounding environment in arrangement and forms. Also residents have the satisfaction and pride in arrangement considering the climate of a region and security of the green space.

Korean Women's Preferences and Emotional Images Associated Fashion Design with Flower Printings (꽃문양이 표현된 패션스타일에 대한 한국 여성의 선호도와 감성이미지)

  • Lim, Si Eun;Kim, Young In
    • Journal of the Korean Society of Costume
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    • v.66 no.2
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    • pp.15-31
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    • 2016
  • Flower images are used as a design motif in various fields. Flower printings in clothes, in particular, usually represent nature. This study sets out to identify the characteristics of different fashion styles with flower printings, as well as the preferences and emotional images of Korean women in their 20s. The flower printings used in fashion design were classified into 5 types of styles: Modern, Natural Romantic, Maximalism, Neo-Hippie, and Ethnic style. Literature review and survey were conducted to identify the emotional images associated with the flower printings, as well as women's preferences. Through literature review, this study noted the formative elements of flower printings and their characteristics, as expressed in fashion designs. Then, the different styles were classified in order to provide theoretical foundation for the survey. The results of the study were significant in that they contributed to the definition and academic systemization of the characteristics of fashion styles with flower printings. Moreover, the study opened up possibilities for utilizing flowers to express a greater variety of meanings and influences in fashion. The findings can be used to enable fashion styles and emotional influences to be expressed through designs using natural motifs besides flowers.

Selection Method of Multiple Threshold Based on Probability Distribution function Using Fuzzy Clustering (퍼지 클러스터링을 이용한 확률분포함수 기반의 다중문턱값 선정법)

  • Kim, Gyung-Bum;Chung, Sung-Chong
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.5 s.98
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    • pp.48-57
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    • 1999
  • Applications of thresholding technique are based on the assumption that object and background pixels in a digital image can be distinguished by their gray level values. For the segmentation of more complex images, it is necessary to resort to multiple threshold selection techniques. This paper describes a new method for multiple threshold selection of gray level images which are not clearly distinguishable from the background. The proposed method consists of three main stages. In the first stage, a probability distribution function for a gray level histogram of an image is derived. Cluster points are defined according to the probability distribution function. In the second stage, fuzzy partition matrix of the probability distribution function is generated through the fuzzy clustering process. Finally, elements of the fuzzy partition matrix are classified as clusters according to gray level values by using max-membership method. Boundary values of classified clusters are selected as multiple threshold. In order to verify the performance of the developed algorithm, automatic inspection process of ball grid array is presented.

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Analysis of Urban Green Areas using NDVI and Development of a Model to Analyze Bird Diversity in Urban Parks (NDVI를 활용한 도시 녹지 분석 및 도시공원 조류 종다양성 분석 모형 개발)

  • Song, Won-Kyong
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.21 no.1
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    • pp.73-82
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    • 2018
  • Urban parks are important bird habitat in cities. Various studies have evaluated the habitat function of urban parks focused on field surveys. In this study, we performed applicability of NDVI obtained from Landsat 8 OLI image as a factor for spatial planning considered bird diversity. This study was classified with green boundary into three groups using NDVI's value. Environmental variables were calculated by the green area ratio of the surrounding area from 100m to 500m at each groups. The 20 environmental variables such as park area, park shape index, canopy of tree, etc. were derived, the regression analysis was performed as a dependent variable for the bird diversity of urban parks. As a result, the park area and the green area ratio of Group 3, classified high NDVI, within the 100m buffer were adopted as the variables in the regression model. In other words, it was confirmed that as the park becomes larger, the distribution of key green areas within a radius of 100m of the parks becomes higher, the diversity of bird species has increased. It was appropriate to use satellite image, NDVI to analyze species diversity in urban area.

A Study of Color Combination based on Fashion Image of Domestic Women's Apparel (국내 여성복 패선 이미지에 따른 배색 연구)

  • Cho Ju-Yeon;Kim Young-In
    • Journal of the Korean Society of Costume
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    • v.56 no.4 s.103
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    • pp.160-170
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    • 2006
  • The purpose of this study is to analyze the image of color combination in fashion design. For this study 14,121 color samples were collected from 116 fashion brands selected by the market segmentation based on the results of the previous studies. The brands have high market share and brand recognition in each segmental market. The color samples were measured by spectrophotometer and analyzed by the Munsell's H V/C and CIE $L^*a^*b^*$ value. The representative colors of each market were selected concerning the tensity in CIE $L^*a^*b^*$ color space and the distance between the color samples. h4 a result, 2,213 representative colors were chosen. These color samples composed top and bottom color combination samples by the program 'Item Comparator' that calculated the color differences$({\Delta}E^*)$. Top includes the items such as blouse, shirt, and coats, bottom includes the items such as skirt and pants. The color combination samples were divided into two groups. In one group ${\Delta}E^*$ was less than 30, and In the other group ${\Delta}E^*$ was 30 or more. For investigating the image of color combination, 480 rotor combination samples were classified. The image adjectives for the survey from preceding studies and brand dictionaries were 'classic', 'modern', 'feminine', 'casual', and 'romantic', which have highly preferred in women's wear brands. The result of the study is as follows; For 'classic' 'image, YR, and greyish tone were generally preferred. In the color combination of 'casual' image, the samples with PB color and greyish tone were preferred. For 'feminine' image, RP was preferred as a top color, R, RP, P were preferred as a bottom color. For 'casual' image, PB was preferred as a top color, PB, B were preferred as a bottom color. For 'romantic' image, RP was preferred as a top color, R, P were preferred as a bottom color. The bigger the color differences between the color combination samples were, the more remarkable the image of color combination samples was.

Image Analysis of Color in Clothes Style (의복스타일별 색채에 대한 이미지 분석)

  • Choi, Jae-Ran;Ryoo, Sook-Hee
    • Journal of the Korean Society of Clothing and Textiles
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    • v.34 no.2
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    • pp.266-279
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    • 2010
  • This research investigates the influence of color as an important factor of the visual image created by clothes. First, the factor analysis of the adjectives describing the images of clothes shows that the images of clothes are classified into 4 factors that include attraction, brightness, femininity, and the figure type (of which the attraction factor and brightness factor were found to be important dimensions). Second, as for the images of feminine style clothes colors, violet appears more refined and attractive than other colors in all 3 tones. Red appears as a brilliant and glowing image in a vivid tone. Yellow in a vivid tone and pale tone, and red in deep tone appear as a warm image, while blue appears as a cold image in all 3 tones. Blue and violet appear as a tall and slim image in all 3 tones. As for the images of mannish style clothes colors, yellow in vivid tone, violet in pale tone and red in deep tone appear as the most refined and attractive image, while green in all the tones appears as a rustic and unattractive image. Red in vivid tone, yellow in pale tone and violet in deep tone appear as a very brilliant and glowing image. Red in pale tone and deep tone appear as a warm and feminine image. Third, yellow in all the tones is evaluated to be attractive in the mannish style in the comparison of the image of feminine and mannish style clothes color, while blue in a pale tone in feminine style and in deep tone in mannish style earned high points. Red and violet did not show any significant differences between the two styles.

Improved Bag of Visual Words Image Classification Using the Process of Feature, Color and Texture Information (특징, 색상 및 텍스처 정보의 가공을 이용한 Bag of Visual Words 이미지 자동 분류)

  • Park, Chan-hyeok;Kwon, Hyuk-shin;Kang, Seok-hoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.79-82
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    • 2015
  • Bag of visual words(BoVW) is one of the image classification and retrieval methods, using feature point that automatical sorting and searching system by image feature vector of data base. The existing method using feature point shall search or classify the image that user unwanted. To solve this weakness, when comprise the words, include not only feature point but color information that express overall mood of image or texture information that express repeated pattern. It makes various searching possible. At the test, you could see the result compared between classified image using the words that have only feature point and another image that added color and texture information. New method leads to accuracy of 80~90%.

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Color Analysis of Avatar fashion style from on-line portal sites

  • Kim, Ri-Ra;Kim, Young-In
    • International Journal of Costume and Fashion
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    • v.8 no.2
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    • pp.50-64
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    • 2008
  • The purpose of this study is to classify Avatar fashion style through analysis of on-line Avatar Mall and to propose color pallette and fashion contents from fashion color analysis. The literature research focused on investigating the notion, characters and types of Avatar and relation of Avatar and self-image, clothing image and color image. In data research, 4 on-line portal sites Avatar Malls were analyzed and Avatar fashion style was classified. In addition, Avatar clothing color was analyzed. The research of this study are as follows: Firstly, Avatar in the cyber space represents 'me' of the real states. Avatar fashion helps to represent Avatar Image and clothing makes human image and identity as a social sign. Color helps to constitute clothing impression and human image, therefore clothing and color are the important elements to express self-image through Avatar in the cyber space. Secondly, Avatar Malls of 4 on-line portal sites are very similar and confuse Avatar users because of no standard of fashion style classification. Accordingly, the standard of fashion style classification should be made by a fashion expert, and the specific characters of every on-line portal site should be emphasized. Thirdly, as a result of the analysis of Avatar's clothing, the clothing is divided into a real world clothing and an imaginary world clothing. There are daily clothes, uniform, event clothes, story clothes and fantasy clothes. As a result of the color analysis of Avatar clothing, White, Red, Red Purple colors and bright and vivid tone are generally used for Avatar clothing. This study is significant to classify Avatar fashion style systematically, to notify sensitive and delicate users' sign and to make Avatar fashion image emotional and high-quality.

The Effect on Satisfaction with Mediation of Trust Caused by Hypermarkets' Online Image (온라인에서 대형마트 쇼핑몰의 이미지가 신뢰를 매개로 만족에 미치는 영향)

  • Shin, Moon-Shik;Kim, Hyo-Jung
    • Journal of Distribution Science
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    • v.12 no.10
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    • pp.67-74
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    • 2014
  • Purpose - This study analyzed how image affects customer trust and satisfaction in the online shopping mall market, which is becoming more competitive; future implications for customer management in online shopping malls were presented. Consumers visit and prefer a few shopping mall sites instead of many sites. Consumers do not visit sites that cannot provide trust and satisfaction. Therefore, establishing trust and satisfaction with differentiated image is essential for survival and growth. Specifically analyzing company image, shop image, and brand image, I studied how symbolic image, functional image, and empirical image affect satisfaction mediated by trust in the online shopping malls of hypermarket retailers. Research design, data, and methodology - To investigate the relationship between image and satisfaction of big box retailers' shopping malls in the online market, the study is based on analyzed data from questionnaires involving advanced research. From May 1st to 20th in the year 2014, a questionnaire survey targeting university students using big box retailers' shopping malls in Seoul was conducted. A total of 282 questionnaires were conducted, and 276 questionnaires were used for empirical analysis, excluding invalid data. Using the SPSS 21.0 statistics package, factor analysis and regression analysis were implemented, and effects of image on trust and satisfaction were presented. Results - First, symbolic image can affect satisfaction with only trust. Among 3 image factors, symbolic image exerts the most influence on trust; trust is important in coupling the medium to satisfaction. Second, functional image and empirical image affect satisfaction directly and indirectly with trust. Conclusions - As I classified the image of hyper market retailers' online shopping malls into symbolic, functional, and empirical image, I analyzed the effects of image on trust and satisfaction empirically. The results of the study and strategic implications are as follows. First, symbolic image can affect satisfaction with only trust. Among 3 image factors, symbolic image exerts the most influence on trust; trust is important in coupling the medium to satisfaction. The establishment of a distinctive symbolic image, such as the online shopping mall's loyalty, level of awareness, and special service, is needed. With the establishment of symbolic image, trust and satisfaction could be improved. Second, functional image and empirical image affect satisfaction directly and indirectly with trust. Especially, as functional image affects trust more than empirical image, setting and implementing a strategy for empirical image based on the right price, service, and convenience could raise trust and satisfaction. Empirical image affects trust and satisfaction substantially. Even though empirical image's influence on trust is lower than that of other three image factors, empirical image's influence on satisfaction is higher than symbolic image. Therefore, it requires a strategy for providing joyful use, and information research functions and distinctive use experience are important to improve satisfaction. This study analyzed image characteristics of hyper-market retailers' online shopping malls in the fast-growing online market; future strategic implications were presented.

Gesture Recognition using Training-effect on image sequences (연속 영상에서 학습 효과를 이용한 제스처 인식)

  • 이현주;이칠우
    • Proceedings of the IEEK Conference
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    • 2000.06d
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    • pp.222-225
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    • 2000
  • Human frequently communicate non-linguistic information with gesture. So, we must develop efficient and fast gesture recognition algorithms for more natural human-computer interaction. However, it is difficult to recognize gesture automatically because human's body is three dimensional object with very complex structure. In this paper, we suggest a method which is able to detect key frames and frame changes, and to classify image sequence into some gesture groups. Gesture is classifiable according to moving part of body. First, we detect some frames that motion areas are changed abruptly and save those frames as key frames, and then use the frames to classify sequences. We symbolize each image of classified sequence using Principal Component Analysis(PCA) and clustering algorithm since it is better to use fewer components for representation of gestures. Symbols are used as the input symbols for the Hidden Markov Model(HMM) and recognized as a gesture with probability calculation.

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