• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.70-75
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• 1993

We represent a method of 3-D object recognition using multi images in this paper. The recognition process is executed as follows. Object models as prior knowledgement are generated and stored on a computer. To extract features of a recognized object, three CCD cameras are set at vertices of a regular triangle and take images of an object to be recognized. By comparing extracted features with generated models, the object is recognized. In general, it is difficult to recognize 3-D objects because there are the following problems such as how to make the correspondence to both stereo images, generate and store an object model according to a recognition process, and effectively collate information gotten from input images. We resolve these problems using the method that the collation on the basis of features independent on the viewpoint, the generation of object models as enumerating some candidate models in an early recognition level, the execution a tight cooperative process among results gained by analyzing each image. We have made experiments based on real images in which polyhedral objects are used as objects to be recognized. Some of results reveal the usefulness of the proposed method.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1807-1810
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• 2003

Steganography based on Just Noticeable Difference(JND) has been used for natural images. However, it has been recognized to have defects for the non-natural images such as scanned text images, cartoons, etc. In this paper, an alternative method is proposed to improve this problem. A new scheme is designed specially for the non-natural images. Instead of JND, Noise Visibility Function(NVF) is used. NVF value and edge strength value of each pixel ate combined to decide the embedding data capacity and the visibility of data embedded images have been improved specially for the non-natural images.

• The Research Journal of the Costume Culture
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• v.15 no.1 s.66
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• pp.113-126
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• 2007

Since the ancient times, black has been the most valuable color. Also, it has played a more important role in a history of fashion than other colors. In general, black was regarded as a color of negative images. However, as people have recognized the aesthetic value of black color, they have expressed unique and various images of black through the medium of clothes. This studies on images of black dress for woman was based on reference to literatures and valid investigations. The images toward black clothing are categorized by study participants' perceptions according to age, marital status and education. The result was as followed. Dignity and modernity were the most frequently cited image of black dress among women followed by feminine, sorrow, sensuality, and abstinence. Age significantly affected the recognition of black dress images. Woman showed significant difference in recognizing dignity, modernity, sensuality, and sorrow in black dress according to their age. Woman more strongly recognize dignity and modernity in black dress when they are younger, while increasingly recognizing abstinence and sensuality in black dress as they become older. Marital status significantly affected woman's recognition of black dress. They showed meaningful difference in recognizing dignity, modernity, and abstinence in black color. In sum, single women recognized more easily dignity and modernity in black dress and less easily abstinence than married women. Women also showed the trend with relation to education level. In general, as women got higher education, they also increasingly recognized dignity and modernity in black dress.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.35-40
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• 1998

This paper describes an automatic recognition method of contents in moving images. The recognition process is carried out by the following two steps. At first, camera works in moving images are analyzed and moving objects are extracted from the moving images. Next, the motion of the object is recognized by pre-procured knowledge. These techniques will be applied to a construction of an efficient image database.

• International Journal of Costume and Fashion
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• v.5 no.1
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• pp.26-41
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• 2005

In this study homosexuality as a discourse represented in contemporary fashion magazines is explored in context. The main concerns are the contemporary construction of homosexuality, fashion symbols to identify homosexuals, and relationships between homosexuality and heterosexual masculinity in fashion images today. After elaborating homosexuality conceptualized historically, an analytical framework from Foucault's discursive approach was made up to interpret the fashion spreads since 2000. As a result, as it is assumed that the concept of homosexuality is constructed by historical specificity, homosexual fashion styles are dynamic. So, it should be recognized that they are formed by power relationships with heterosexuality, and other social factors such as class, race, age, and consumer culture and market trends. On the basis of photographic themes and fashion looks homosexual images are classified into 3 kinds of versions, the effeminate trend setter, the masculine athlete or biker, and the neo camp. However, most of contemporary homosexual photographs are not also so conspicuously different from heterosexual ones. Therefore, in the contemporary structure at least from fashion images, homosexuals can be recognized equally with heterosexual people only except for sexual preference. Thus, homosexual fashion also shares a lot of fashionable products with heterosexual one, with often homosexuals' role as trend -setter.

• Journal of the East Asian Society of Dietary Life
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• v.20 no.6
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• pp.837-844
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• 2010

Dietary life was formed as being influenced by the people's cultural, social and environmental situations. The people's food culture is unique that was adapted to their surroundings. It was developed and industrialized in the ethnic food. Now the ethnic food was contributed to tour industry or culture industry. Then, food life style was change from the meat diet to the vegetable diet in the diffusion of well-being trends. So, we analyzed Koreans' Korean food image and investigated the difference as a demographics. We made questionnaire and did a survey to 220 bloggers using cooking internet sites on 10 August, 2009. We analyzed 206 questionnaires by SPSS package 12.0 except 14 untrustworthy questionnaires. We measured credibility and validity 39 items related Korean food image: Chronbach's ${\alpha}$ was highly 0.855. We checked that KMO examination was 0.775 and $x^2$ of Barttlet was 2482.342. After verymax rotation, we deducted 5 Koran food images-healthy, visuality, spicy, variety, low calorie. We analyzed ANOVA of 5 Korean food images according to demographics. We confirmed the differences by ages, monthly income and job except academic background (p<0.05). Therefore, Korean food images were learned and recognized in everyday life. Especially, we found that visuality and variety were recognized the more stronger high-income earners and teachers than others. So, Korean learned Korean food images in real life and recognized Korean food quite differently by demographics.

• Journal of the Korea Fashion and Costume Design Association
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• v.22 no.1
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• pp.97-111
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• 2020

Classifying clothing fabrics into fashion images lacks research, but is necessary due to the short cycle of fashion and rapidly changing modern trends as consumers seek to satisfy various needs with an increase of online purchases. There is also a lack of research on fashion trend books which attach real fabrics. Therefore, this study aims to help the planning field by recognizing fabric sensibility related to the fabric image perceived by consumers. The data analysis results from descriptive statistics, t-test, and ANOVA using SPSS are as follows: Differences in the visual tactility evaluation related to the consumer recognized fabric images showed more significant differences in F/W seasons. The elegance image was shown as relatively thick, the avant-garde image was shown as relatively heavy, thick fabric. The feminine image was shown as relatively thin and smooth fabric, the sporty images were shown to be moist, flexible and elastic, and the mannish images were relatively rough. The romantic images were shown as relatively thin fabrics. The conclusions inferred from the visual tactile evaluation related to the fabric images recognized by consumers vary by major, so the prior information concerning fabrics and trends can affect the selection of images. The results of this study show that in order to produce clothes suitable for fashion product planning by learning about visual tactility that consumers recognize, fabrics component data displayed in fashion trend books from 2016 to 2018 are needed, so the planner can receive help when selecting the fabrics suitable for each trend.

• Journal of dental hygiene science
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• v.17 no.2
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• pp.108-115
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• 2017

The purpose of this study was to investigate the influence of dental hygienist images and career advice among high school teachers. A self-reported questionnaire was administered to 212 high school teachers in Gwangju, South Korea. The questionnaire contained subject's general characteristics, images of dental hygienists, and career advice. We performed an independent t-test, the Kruskal-Wallis test, Pearson's correlation coefficient, multiple regression analysis, and logistic regression analysis using the IBM SPSS ver. 21.0 software. Using a five-point scale, the average of all the dental hygienist images was 3.50, with personal images receiving the most positive rating at 3.83 and social images receiving the least positive rating at 2.86. The images of dental hygienists were significantly more positive in instances where the subjects recognized the dental hygienist or received treatment within one year. There were positive correlations among different kinds of images. Through multiple regression analysis, occupational images were associated with business and social images. Business images were associated with occupational and personal images. Personal images were associated with business images, especially in cases where the subjects recognized the dental hygienist. Social images were associated with occupational images, especially in cases where subjects received treatment within one year. Through logistic regression analysis, career advice was associated with social and occupational images. Therefore, our study provides suggestions on how to enhance positive recognition of social images of dental hygienists.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.525-527
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• 2003

Recently, the spatial resolution of earth observation satellites is significantly increased to a few meters. Such high spatial resolution images definitely will provide lots of information for detail-thirsty remote sensing users. However, it is more difficult to develop automated image algorithms for automated image feature extraction and pattern recognition. In this study, we propose a two-stage procedure to extract road information from high resolution satellite images. At first stage, a watershed segmentation technique is developed to classify the image into various regions. Then, a knowledge is built for road and used to extract the road regions. In this study, we use panchromatic and multi-spectral images of the IKONOS satellite as test dataset. The experiment result shows that the proposed technique can generate suitable and meaningful road objects from high spatial resolution satellite images. Apparently, misclassified regions such as parking lots are recognized as road needed further refinement in future research.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.232-241
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• 2014

This paper proposes an underwater localization algorithm using probabilistic object recognition. It is organized as follows; 1) recognizing artificial objects using imaging sonar, and 2) localizing the recognized objects and the vehicle using EKF(Extended Kalman Filter) based SLAM. For this purpose, we develop artificial landmarks to be recognized even under the unstable sonar images induced by noise. Moreover, a probabilistic recognition framework is proposed. In this way, the distance and bearing of the recognized artificial landmarks are acquired to perform the localization of the underwater vehicle. Using the recognized objects, EKF-based SLAM is carried out and results in a path of the underwater vehicle and the location of landmarks. The proposed localization algorithm is verified by experiments in a basin.