• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.363-364
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• 2021

Search technology is applied to various applications using artificial intelligence technology. It is used in many ways, from identifying customer preferences to personalized recommendation systems. The purpose of this study is to develop a system for detecting adult males mainly in children's living spaces. This will prevent dangerous situations of adult intruders in advance and can be used for outsider control system. In order to develop such a system, information about clothes is used, and adult detection system is developed using various factors such as color, pattern, fashion style, and size of clothes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.653-654
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• 2022

Recently, technology development using artificial intelligence (AI) is being conducted in various fields. It is being used in many areas, from a personalized recommendation system for general personal taste to the development of application technology that meets a specific purpose. In this study, for adult detection, we propose a method for detecting adults in elementary schools where many elementary school students live. Clothing color, pattern, style, or physical size are used as factors to differentiate between adults and children, and through this, it will be possible to quickly detect adults or unauthorized adults who break into elementary schools and use them in the pre-recognition system.

• Journal of Internet Computing and Services
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• v.9 no.5
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• pp.117-130
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• 2008

This paper proposes a stable and robust method to distinct the color similarity for clothes using the LBG algorithm under various light sources, Since the conventional methods, such as the histogram intersection and the accumulated histogram, are profoundly sensitive to the changing of light environments, the distinction of color similarity for the same cloth can be different due to the complicated light sources. To reduce the effects of the light sources, the properties of hue and saturation which consistently sustain the characteristic of the color under the various changes of light sources are analyzed to define the characteristic of the color distribution. In a two-dimensional space determined by the properties of hue and saturation, the LBG algorithm, a non-parametric clustering approach, is applied to examine the color distribution of images for each clothes. The color similarity of images is defined by the average of Euclidean distance between the mapping clusters which are calculated from the result of clustering of both images. To prove the stability of the proposed method, the results of the color similarity between our method and the traditional histogram analysis based methods are compared using a dozen of cloth examples that obtained under different light environments. Our method successively provides the classification between the same cloth image pair and the different cloth image pair and this classification of color similarity for clothe images obtains the 91.6% of success rate.

• The Research Journal of the Costume Culture
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• v.6 no.1
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• pp.94-109
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• 1998

The objective of this study is to measure self-image of adolescence, analyze empirically clothing-purchasing-behavior of adolescence and clarify correlation of two variables, self-image and clothing-purchasing-behavior. For this purpose, the techniques involve theoretical studies and researches based on historical obtained from previous related studies and surveys, 431 high school female students who reside in Seoul are asked to answer selected survey questions to examine three aspects, clothing-purchasing-behavior, self-image and demographics. The evaluation of surveyed information is analyzed by statistical techniques to improve the accuracy of data. Statistical methods used are as follows; Descriptive(frequency, mean, percentage), Factor Analysis(varimax rotation), Crosstabs(Chi-square), T-test, One-Way ANOVA< Correlation Analysis, Reliability Analysis and Duncan's Multiple Range Test. The mjor results of this study were as follows: Firstly, there is a discrepancy between real self-image and ideal self-image. Furthermore more significant differences is seen from physical aspects than psychological aspects. Consequently, research proves that the difference derived from their ideal situation and real situation leads to psychological unstableness. In addition, making their real self-image is dependent upon several elements such things as family economic level, pocket money, expenditure on clothing. Therefore, it is critical to combine all factors in order to decide how much to spend for children's clothing and pocket money in parents point of view. Secondly, research shows that shows hat there is correlated relationship between average expenditure on clothing and presence of mother's job. Average expenditure on clothing is, generally, influenced by vogue which is tend to be changed seasonally. It, also, shows that there is positive linear regression between expenditure on clothe and sensitivity for vogue. That is to say, dependent variable, expenditure on clothing, is varied as independent variable, sensitivity for vogue, changes. Female high school students are likely to give much value on brand. Moreover people who are spending more money on clothes have higher tendencies in prompt purchases than who are not. Thirdly, the analysis of clothing-purchasing-behavior and self-image shows that the difference between real self-image and ideal self-image draws the main reason of dissatisfaction after purchase of clothes. As a consequence, their unfilled needs lead them to keep making another purchase to satisfy themselves. Therefore, it is strongly recommended that parents' advices and directions on their children's money spending on clothes are imperative to establish well-behaved purchasing patterns.

• Management & Information Systems Review
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• v.31 no.3
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• pp.223-248
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• 2012

This study analyses support policy and structural change of textile industry in Daegu Kyungbuk region, and suggests major issues for textile industry's innovation. In Daegu Kyungbuk, it was 1999 that a policy, so called Milano Project, in order to promote a textile industry was devised. In 2004, the Regional Industrial Promotion Plan was devised. The plan was born from a view point of establishing a regional innovation system and of promoting the innovative clusters under a knowledge based economy. After then, the Regional Industry Promotion Project or Regional Strategic Industry Promotion Project became a core of regional textile industrial policy. Research results indicated that the first stage Milano project (1999-2003) showed both positive and negative effects. There were no long-term development plan, clear vision and strategy. But, core industrial infrastructure for differentiated product development, such as New product Development Support Center and Dyeing Design Practical Application Center, was constructed. The second stage Daegu Textile Industry Promotion Plan (2004-2008) displayed a significant technological performance and new product sales with the assistance of Kyungbuk province. Also, textile industry revealed positive fruits such as financial structure, productivity, and profitability as a result of strong restructuring. In industrial structure, there was a important change from clothe textile material to industry textile material. Most of textile companies did not showed high capability in CEO's technology innovation intention, entrepreneurship, R&D and human resource competency in compare with other industry. We suggested that Daegu Kyungbuk has to select and concentrate on the high-tech textile material and living textile for sustainable development and competitiveness. We also proposed a confidence and cooperation based innovation network and company oriented innovation cluster.