• Journal of Fashion Business
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• v.28 no.2
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• pp.33-49
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• 2024

Despite COVID-19 and the global economic depression, cosmetics exports are continuously increasing due to the growth of Hallyu consumption overseas. Thus, systematic research is needed to determine what impact Hallyu has on cosmetics. Many studies have been conducted on psychological distance, Hallyu preference, and the overall Korean product image, but research related to the image of cosmetics has been insufficient. AMOS 26.0 was used to empirically analyze the impact of cultural distance, social distance, and Hallyu preference on the national image and the impact of the country's image on the image of cosmetics among females experienced with Hallyu in Indonesia and Malaysia. The empirical analysis showed that cultural distance, social distance, and Hallyu preference had a positive effect on the national image, and the national image also had a positive effect on the image of cosmetics. Since Hallyu has a positive indirect effect on the image of cosmetics, it strengthens the competitiveness of cosmetics companies in overseas markets. In Indonesia, only cultural distance and Hallyu preference were found to affect the national image. However, in Malaysia, all variables affected the national image. Thus, even the same Hallyu content could have different effects on the national and cosmetic images in each country. Therefore, strategies for utilizing different Hallyu contents that are suitable for each country are needed to revitalize Korean cosmetics in overseas markets.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.83-88
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• 2006

Digital image processing algorithm was proposed to measure the area inside of an object image using angle-distance graph used to analyze the pattern of an object in the digital image processing techniques. The first angle-distance graph is generated from a point inside of an object area. The second angle-distance graphs are generated for the areas missed in the first graph by extracting the positions with large gradient in the first angle-distance graph. The order of the graph increases according to the complexity of an object pattern. Size of the area inside of an object boundary is measured by integrating square of distance multiplied by angle for each area from the hierarchical angie-distance graphs.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.323-328
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• 2011

For content-based image retrieval, the earth mover's distance and the optimal color composition distance are proposed to measure the dissimilarity. Although providing good retrieval results, both methods are too time-consuming to be used in a large image database. To solve the problem, we propose a new distance function that calculates an approximate earth mover's distance in linear time. To calculate the dissimilarity in linear time, the proposed approach employs the space-filling curve. We have performed extensive experiments to show the effectiveness and efficiency of the proposed approach. The results reveal that our approach achieves almost the same results with the EMD in linear time.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.65-72
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• 2000

In this paper we propose the new binary image matching algorithm called the Fuzzy logic induced Hausdorff Distance(FHD) for finding the maximally matched image with the query image. The membership histogram is obtained by normalizing the cardinality of the subset with the corresponding radius after obtaining the distribution of the minimum distance computed by the Hausdroff distance between two binary images. in the proposed algorithm, The fuzzy influence method Center of Gravity(COG) is applied to calculate the best matching candidate in the membership function described above. The proposed algorithm shows the excellent results for the face image recognition when the noise is added to the query image as well as for the character recognition.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.137-145
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• 2014

This paper suggests an LDA-based long distance face recognition algorithm for intelligent surveillance system. The existing face recognition algorithm using single distance face image as training images caused a problem that face recognition rate is decreased with increasing distance. The face recognition algorithm using face images by actual distance as training images showed good performance. However, this also causes user inconvenience as it requires the user to move one to five meters in person to acquire face images for initial user registration. In this paper, proposed method is used for training images by using single distance face image to automatically create face images by various distances. The test result showed that the proposed face recognition technique generated better performance by average 16.3% in short distance and 18.0% in long distance than the technique using the existing single distance face image as training. When it was compared with the technique that used face images by distance as training, the performance fell 4.3% on average at a close distance and remained the same at a long distance.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.379-383
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• 2015

This paper presents an approach to detect object distance with the use of the recently developed low-cost Kinect sensor. The technique is based on Kinect color depth-image processing and can be used to design various computer-vision applications, such as object recognition, video surveillance, and autonomous path finding. The proposed technique uses keypoint feature detection in the Kinect depth image and advantages of depth pixels to directly obtain the feature distance in the depth images. This highly reduces the computational overhead and obtains the pixel distance in the Kinect captured images.

• Journal of Korea Multimedia Society
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• v.11 no.6
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• pp.764-776
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• 2008

Image identification is the process of checking whether the query image is the transformed version of the specific original image or not. In this paper, image identification method based on feature composition is proposed. Used features include color distance, texture information and average pixel intensity. We extract color characteristics using color distance and texture information by Modified Generalized Symmetry Transform as well as average intensity of each pixel as features. Individual feature is quantized adaptively to be used as bins of histogram. The histogram is normalized according to data type and it is used as the signature in comparing the query image with database images. In matching part, Manhattan distance is used for measuring distance between two signatures. To evaluate the performance of the proposed method, independent test and accuracy test are achieved. In independent test, 60,433 images are used to evaluate the ability of discrimination between different images. And 4,002 original images and its 29 transformed versions are used in accuracy test, which evaluate the ability that the proposed algorithm can find the original image correctly when some transforms was applied in original image. Experiment results show that the proposed identification method has good performance in accuracy test. And the proposed method is very useful in real environment because of its high accuracy and fast matching capacity.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.621-624
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• 1999

This paper describes a distance estimation method of object's motion in soccer image sequence by tracking field features. And we quantitatively evaluate the estimation accuracy We suppose that the input image sequence is taken with a camera on static axis and includes only zooming and panning transformation between frames. Adaptive template matching is adopted for non-rigid object tracking. For background compensation, feature templates selected from reference frame image are matched in following frames and the matched feature point pairs are used in computing Affine motion parameters. A perspective displacement field model is used for estimating the real distance between two position on Input Image. To quantitatively evaluate the accuracy of the estimation, we synthesized a 3 dimensional virtual stadium with graphic tools and experimented on the synthesized 2 dimensional image sequences. The experiment shows that the average of the error between the actual moving distance and the estimated distance is 1.84%.

• The Journal of the Korea Contents Association
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• v.6 no.10
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• pp.53-61
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• 2006

Culture, consumers' value and attitude play an important role for global marketing strategy on cross-cultural perspectives. The aim of this research was to investigate how consumer ethnocentrism and cultural affinity affect psychic distance, country image and competitive brand choice. data were collected through personal interview. A total of 234 responses are put to final analysis. The results are as follows: First, cultural affinity play an important role for psychic distance and country image. Second, consumer ethnocentrism has directly affected country image and psychic distance. Finally, country image has affected competitive brand choice, but psychic distance doesn't have affected.

• Korean Journal of Digital Imaging in Medicine
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• v.14 no.1
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• pp.37-42
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• 2012

Pediatric head and neck phantom, using the rate by focusing distance and grid images, Image J using the Quality Assessment and Dose Area Product compared. X-ray laboratory equipment due to the Philips Digital DIAGNOST a 110 cm FFD set and using ACE Non-grid, focusing distance 110 cm (12 : 1), 140 cm (12 : 1), 180 cm (8 : 1) Focused grid, Acryl Phantom (Fluke Model 76-2 Series Phantom) 15.24 cm, by resolution chart image acquisition, image evaluation program (Image J Ver. 1.4.3.67, USA) imaging experiments were analyzed using. Dose Area Product in the Non Grid 0.028 $mGy{\cdot}cm^2$, focusing distance 110 cm (12 : 1), the 0.129 $mGy{\cdot}cm^2$, 140 cm (12 : 1), the 0.135 $mGy{\cdot}cm^2$, 180 cm (8 : 1) was measured with a 0.110 $mGy{\cdot}cm^2$ Non Grid, focusing distance 110 cm (12 : 1), 140 cm (12 : 1), 180 cm (8 : 1) Image obtained when grid using the image J program focusing distance 110 cm with grid based on the measured SNR and PSNR Non Grid if the SNR the 17.307 dB, PSNR of the 20.002 dB, if the SNR 28.755 dB, PSNR was measured by the 31.451 dB. Image J image analysis through the streets, rather than focusing on grid by the rate that could see an increase in dose. Select the grid by a small dose rate reduction is possible.