• Journal of Distribution Science
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• v.13 no.9
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• pp.59-70
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• 2015

Purpose - This study aims to suggest strategies for Korean enterprises advancing into the Vietnam bakery market by analyzing the effects of perceived values on brand preference and purchase intention among Korean and Vietnamese consumers. Research design, data, and methodology - The perceived value model designed includes functional (price, quality), emotional, and social values. The survey collected data from 500 consumers in Seoul (Korea) and HoChiMinh (Vietnam). The SPSS 18.0 package was used for analysis. Results - First, among Vietnamese consumers, perceived value had a positive (+) effect on global brand preference in the order of functional value of quality, social value, and the functional value of price. However, from an ethnocentric trend and brand image origin, emotional value had a negative effect on global brand preference. In contrast, among Korean consumers, perceived value had a positive (+) effect on global brand preference in the order of functional value of quality, the functional value of price, and the social value. However, emotional value had no effect on global brand preference. Second, for both Korean and Vietnamese consumers, perceived value had a significant positive effect on purchase intention. Third, unlike the Korean consumer, for the Vietnamese consumer, global brand preference had a significant effect on purchase intention. Conclusions - The study implies the following. First, the Vietnamese bakery market has a high proportion of middle-aged customers in their 40s (64%). In terms of monthly income, there was a large proportion (40%) of high-income earners (over $325). Therefore, bakery consumption can be seen as concentrated among middle-aged and high-income consumers. Based on this, bakery strategies should include efforts to increase purchase prices as well as ways to attract local consumers (large cities). Second, unlike Korean consumers, among Vietnamese consumers, the resistance to a global brand based on emotional value (the ethnocentric tendency and brand image origin) can be seen as relatively low. Thus, in the case of the Vietnam bakery market, to increase a global brand's preference, the company should develop a differentiated strategy so that Vietnamese consumers can recognize it better, focusing on product quality, good service quality, and price in the local environment and on social value for social development. Third, in the case of the Vietnamese customer, we found that social value exerts the greatest influence on purchase intention. Therefore, a brand that engenders an image of building the local Vietnamese community can achieve a higher social value and influence purchase intention. In addition, although Vietnamese consumers have ethnocentric tendencies in terms of products, we found that if it is a preferred global brand then there are intentions to purchase. Fourth, in the case of Vietnam, if the preference for global brands is formed, consumer awareness may be connected to purchase intention. Therefore, global brands operating in Vietnam should pay attention to how to improve consumer preferences for global brands in order to increase purchase intention.

• Journal of Korea Multimedia Society
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• v.19 no.9
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• pp.1659-1668
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• 2016

Understanding 3D structure of scenes is of a great interest in various vision-related tasks. In this paper, we present a unified approach for estimating depth from a single monocular image. The key idea of our approach is to take advantages both of parametric learning and non-parametric sampling method. Using a parametric convolutional network, our approach learns the relation of various monocular cues, which make a coarse global prediction. We also leverage the local prediction to refine the global prediction. It is practically estimated in a non-parametric framework. The integration of local and global predictions is accomplished by concatenating the feature maps of the global prediction with those from local ones. Experimental results demonstrate that the proposed method outperforms state-of-the-art methods both qualitatively and quantitatively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3981-4004
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• 2019

This paper proposes a novel method for locating objects in real space from a single remote image and measuring actual distances between them by automatic detection and perspective transformation. The dimensions of the real space are known in advance. First, the corner points of the interested region are detected from an image using deep learning. Then, based on the corner points, the region of interest (ROI) is extracted and made proportional to real space by applying warp-perspective transformation. Finally, the objects are detected and mapped to the real-world location. Removing distortion from the image using camera calibration improves the accuracy in most of the cases. The deep learning framework Darknet is used for detection, and necessary modifications are made to integrate perspective transformation, camera calibration, un-distortion, etc. Experiments are performed with two types of cameras, one with barrel and the other with pincushion distortions. The results show that the difference between calculated distances and measured on real space with measurement tapes are very small; approximately 1 cm on an average. Furthermore, automatic corner detection allows the system to be used with any type of camera that has a fixed pose or in motion; using more points significantly enhances the accuracy of real-world mapping even without camera calibration. Perspective transformation also increases the object detection efficiency by making unified sizes of all objects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.997-1003
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• 2007

In this paper, we propose a global approach for automatic inspection of defects in the polarizer film image. The proposed method does not rely on local feature of the defect. It is based on a global image reconstruction scheme using the singular value decomposition(SVD). SVD is used to decompose the image and then obtain a diagonal matrix of the singular values. Among the singular values, the first singular value is used to reconstruct a image. In reconstructed image, the normal pixels in background region have a different characteristics from the pixels in defect region. It is obtained the ratio of pixels in the reconstructed image to ones in the original image and then the defects are detected based on the the statistical process of the ratio. The experiment results show that the proposed method is efficient for defect inspection of polarizer lam image.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.3
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• pp.427-439
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• 2019

This study investigated the semantic network based on the focus of the fashion image and SNS text utilized by global SPA brands on the last seven years in terms of the quantity and quality of data generated by the fast-changing fashion trends and fashion content-based media environment. The research method relocated frequency, density and repetitive key words as well as visualized algorithms using the UCINET 6.347 program and the overall classification of the text related to fashion images on social networks used by global SPA brands. The conclusions of the study are as follows. A common aspect of global SPA brands is that by looking at the basis of text extraction on SNS, exposure through image of products is considered important for sales. The following is a discriminatory aspect of global SPA brands. First, ZARA consistently exposes marketing using a variety of professions and nationalities to SNS. Second, UNIQLO's correlation exposes its collaboration promotion to SNS while steadily exposing basic items. Third, in the case of H&M, some discriminatory results were found with other brands in connectivity with each cluster category that showed remarkably independent results.

• Journal of the Korean Society of Food Culture
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• v.23 no.6
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• pp.720-728
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• 2008

The objective of this article is to examine Korean consumers' perception level of the country-of-origin of brand (COB) of global restaurant franchises. Although global brands have rushed onto the Korean food service market since 1980, there has been little or no research conducted regarding consumers' perception of COB of global restaurant franchises. In this study, we surveyed consumers to determine their perception of COB for 27 foreign global restaurant brands; specifically, we attempted to determine whether or not Korean consumers could correctly recognize the COB of each brand. The results of this research revealed that Korean consumers correctly perceived the COB of certain restaurant brands, and incorrectly perceived some other brands. For instance, Korean consumers' perception level of the COB of McDonald's and KFC were quite high, and conversely their perceptions of the COB of Outback Steakhouse and Pohoa were relatively low. When consumers select a restaurant brand, COB image was shown to be more influential than brand image.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.56
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• pp.3-27
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• 2012

The purpose of this thesis is to develop a relational model which can explain consumer selection for exporting goods and analyze the effect of corporate image on the relations between country image and consumer selection under global trade environment. The specific objectives are as follows: 1) to suggest a concept of consumer selection and measurement criteria, 2) to analyze correlations among country image, corporate image and consumer selection and 3) to find out the effect of corporate image on the relations between country image and consumer selection. The SPSS program for window and LISREL program were used to analyze the data for this study. The statistical method used in this study was the covariance structure analysis estimating parameters by maximum likelihood method. Path coefficients were tested for t-tests with a statistical significance level of .05. The conclusions of this study are as follows. First, significant correlations were observed among all sub-variables proposed in this study. In addition, significant correlations were detected among country image, consumer selection and corporate image. Second, a hypothetical model proposed in this study was mostly appropriate. Country image had a positive direct effect on consumer selection and corporate image with statistical significance. In addition, it has an indirect impact on consumer selection with statistical significance with corporate image as an intervening variable. Third, corporate image had a significant moderation effect in country image-consumer selection relations. As corporate image levels increased, the effect of country image on consumer selection increased as well. In other words, it has been confirmed that if corporate image levels are high, country image could end up with consumer selection.

• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.1-14
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• 2011

While the circulation of images become active, various requirements to manage increasing database are raised. The content-based technology is one of methods to satisfy these requirements. The image is represented by feature vectors extracted by various methods in the content-based technology. The global feature method insures fast matching speed because the feature vector extracted by the global feature method is formed into a standard shape. The global feature extraction methods are classified into two categories, the spatial feature extraction and statistical feature extraction. And each group is divided by what kind of information is used, color feature or gray scale feature. In this paper, we introduce various global feature extraction technologies and compare their performance by accuracy, recall-precision graph, ANMRR, feature vector size and matching time. According to the experiments, the spatial features show good performance in non-geometrical modifications, and the extraction technologies that use color and histogram feature show the best performance.

• Journal of the Chungcheong Mathematical Society
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• v.22 no.2
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• pp.177-186
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• 2009

The global least squares method (Gl-LSQR) is a generalization of LSQR method for solving linear system with multiple right hand sides. In this paper, we present how to apply this algorithm for solving the image restoration problem and illustrate the usefulness and effectiveness of this method from numerical experiments.

• International Journal of Costume and Fashion
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• v.6 no.1
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• pp.56-70
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• 2006

The purpose of this study was to develop the high-value-added fashion cultural products with Korean image for the enhancement of global competitiveness. For this purpose, theoretical examination of the unique beauty of Korea and Korean image was first performed. Especially, characteristics of Korean traditional botanic patterns were investigated with LOHAS(Lifestyles of Health and Sustainability) philosophy which is the focus of the current design trend. Along with the above, the environmentally-friendly digital textile printing technology and Korean traditional botanic patterns were used to produce creative and globally-competitive fashion cultural products. Finally, a series of fashion cultural products were developed such as table runner, table mat and bedclothes.