• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.101-111
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• 1994

The human face can provide a great deal of information in regard to his/her race, age, sex, personality, feeling, psychology, mental state, health condition and ect. If we pay a close attention to the aging process, we are able to find out that there are recognizable phenomena such as eyelid drooping, cheek drooping, forehead furrowing, hair falling-out, the hair becomes gray and etc. This paper proposes that the method to estimate the age by analyzing these feature components for the facial image. Ang we also introduce the method of facial image synthesis in accordance with the cange of age. The feature components according to the change of age can be obtainec by dividing the facial image into the 3-dimensional shape of a face and the texture of a face and then analyzing the principle component respectively using 3-dimensional model. We assume the age of the facial image by comparing the extracted feature component to the facial image and synthesize the resulted image by adding or subtracting the feature component to/from the facial image. As a resurt of this simulation, we have obtained the age changed ficial image of high quality.

• Journal of Fashion Business
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• v.12 no.1
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• pp.30-44
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• 2008

The purpose of this study is to investigate the effect of eyeshadow color(brown, purple), lipstick color(red, red purple, and yellow red), and lipstick tone(vivid, light, dull, and dark), clothing tone(vivid, light, dull, and dark) on image formation. Sets of stimulus and response scales(7 point semantic) were used as experimental materials. The stimuli were 64 color pictures manipulated with the combination of eyeshadow color, lipstick color, lipstick tone, and clothing tone using computer simulation. The subjects were 384 female undergraduates living in Gyeongnam-do. Image factor of the stimulus was composed of 4 different components (attractiveness, visibility, gracefulness, and tenderness). In the 4 image components, eyeshadow color and clothing tone showed independent effect. Lipstick tone influenced independently on the visibility and tenderness. In the contrast color coordination of clothing and makeup, visibility image by the coordination of lipstick color with lipstick tone, lipstick color with clothing tone or lipstick tone with clothing tone, gracefulness image by the coordination of eyeshadow color with lipstick color, tenderness image can be produced by the coordination of eyeshadow color with lipstick color, eyeshadow color with lipstick tone or eyeshadow color with clothing tone.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.366-381
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• 2013

This paper is to identify how variety of products, product quality, guarantees, employee services and physical environment of store which is considered to store image components influence on satisfaction and loyalty, which in turn effects on loyalty in grocery retailing stores. A survey was conducted to collect the data with consumers who had the actual purchase experience within 1 years in grocery retailing stores. Analysis of structural equation modeling with SPSS 19.0 and AMOS 16.0 were performed to test the research hypothesis. The result of the study as follows: First, product quality and employee services influence on both satisfaction and trust, but physical environment of store are effects on satisfaction only. Second, no store image components influence on loyalty. Finally, satisfaction was effect on both trust and loyalty, whereas trust was not effect on loyalty. In order to build strong customer loyalty, marketer have to strengthen the relationship quality such as satisfaction and trust, and formed through store image components that is much stronger on loyalty.

• Resources Recycling
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• v.30 no.4
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• pp.3-10
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• 2021

The field of recycling for waste electronic components, which is the typical example of an urban mine, requires the development of useful sorting techniques. In this study, a sorter based on image identification by deep learning was developed to select electronic components into four groups. They were recovered from waste printed circuit boards and should be separated to depend on the difference after treatment. The sorter consists of a workstation with GPU, camera, belt conveyor, air compressor. A small piece (less than 3.5 cm) of electronic components on the belt conveyor (belt speed: 6 cm/s) was taken and learned as teaching data. The accuracy of the image identification was 96% as kinds and 99% as groups. The optimum condition of sorting was determined by evaluating accuracies of image identification and recovery rates by blowdown when changing the operating condition such as belt speed and blowdown time of compressed air. Under the optimum condition, the accuracy of image classification in groups was 98.7%. The sorting rate was more than 70%.

• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.98-109
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• 2010

Research on the construction, measurement, and management of brand equity has been extensive since David A. Aaker(1991) and Kevin Lane Keller(1993) first advanced the concept. Recently, much attention has been devoted to the components of brand equity: brand awareness, perceived quality, brand image, and brand loyalty. This study explores the relationships among these components, focusing particularly on the moderating role of product type (utilitarian vs. hedonic) in their causal relationships. A model to study the relationship among components of brand equity, particularly the moderating role of product type, is featured in Figure 1. The hypotheses of the study are proposed as follows: that consumers' brand awareness has a positive influence on brand loyalty and brand image; that consumers' perceived quality has a positive influence on brand loyalty and brand image; that consumers' brand image influences brand loyalty positively; and that relationships among components of brand equity will be moderated by product type. That is, in the case of utilitarian products, the impact of perceived quality on brand loyalty will be relatively stronger, whereas with hedonic products the impact of brand image on brand loyalty will be relatively stronger. To determine the products for the study, a pre-test of 58 college students in the Seoul metropolitan area was conducted based on the product type scale. As a result, computers were selected as the utilitarian product and blue jeans became the hedonic product. For each product type, two brands were selected: Samsung and HP for computers, and Levis and Nix for blue jeans. In the main study, 237 college students in the metropolitan area were surveyed to measure their brand awareness, perceived quality, brand image, and brand loyalty toward the selected two brands of each product type. The subjects were divided into two groups: one group (121 subjects) for computers, the other (116 subjects) for blue jeans. The survey questionnaires for the study included four parts: five questions on brand awareness and four questions each on perceived quality, brand image, and brand loyalty. All questions were to be answered using 7-point Likert scales. The data collected by the survey were processed to assess reliability and validity, and the causal relationships were analyzed to verify the hypotheses using the AMOS 7 program, a tool for analyzing structural equation modeling. A confirmatory factor analysis assessed the appropriateness of the measurement model, and the fit indices denoted that the model was satisfactory. The relationships among the components of brand equity were also analyzed using AMOS 7. The fit indices of the structural model denoted that it was also satisfactory. The paths in the structural model as will be seen in Figure 2 show that perceived quality affects brand image positively, but that brand awareness does not affect brand image. Moreover, it shows that brand awareness, perceived quality, and brand image are positively related with brand loyalty, and that this relationship is moderated by product type. In the case of utilitarian products, perceived quality has relatively more influence on brand loyalty. Conversely, in the case of hedonic products, brand image has relatively more influence on brand loyalty. The results of this empirical study contribute toward the advancement of our understanding of the relationships among the components of brand equity and expand the theoretical underpinnings for brand equity measurement. It also helps further our understanding of the effect of product type on customer-based brand equity. In a marketing management practice perspective, these results may provide managerial implications for building and maintaining brand equity effectively.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.27 no.1
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• pp.56-74
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• 2023

In order to obtain practical and high-quality satellite images containing high-frequency components, a large aperture optical system is required, which has a limitation in that it greatly increases the payload weight. As an attempt to overcome the problem, many multi-aperture optical systems have been proposed, but in many cases, these optical systems do not include high-frequency components in all directions, and making such an high-quality image is an ill-posed problem. In this paper, we use deep learning to overcome the limitation. A deep learning model receives low-quality images as input, estimates the Point Spread Function, PSF, and combines them to output a single high-quality image. We model images obtained from three rectangular apertures arranged in a regular polygon shape. We also propose the Modulation Transfer Function Loss, MTF Loss, which can capture the high-frequency components of the images. We present qualitative and quantitative results obtained through experiments.

• Asia Marketing Journal
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• v.16 no.1
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• pp.169-193
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• 2014

The earlier studies have verified that brand values have significant impact on financial values such as stock return and stock price to justify marketing costs for brand building. Except for Mizik and Jacobson (2008), however, little research has addressed what kinds of brand components composing brand values have a significant relationship with financial values. As a follow-up research of Mizik and Jacobson (2008), this research focuses on what kinds of relationships exist between the unanticipated change of each brand asset component and stock return, one of the financial values. The authors selected six brand asset components from the Korea-Brand Power Index(K-BPI) data in which 'Top of Mind,' 'Unaided Awareness,' and 'Aided Awareness' are brand awareness measures and 'Image,' 'Purchase Intention,' and 'Preference' are brand loyalty measures. Out of those six brand components, they found that unanticipated changes of 'Top of Mind,' 'Unaided Awareness,' 'Image,' and 'Preference' have significantly positive effect on unexpected stock return change. Therefore, they conclude that these four brand asset components provide incremental information in explaining unanticipated stock return.

• Journal of Broadcast Engineering
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• v.11 no.1 s.30
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• pp.91-99
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• 2006

Pre-processing is one of image processing techniques to enhance image quality or appropriately convert a given image into another form for a specific purpose. An 8 bit depth map obtained by a depth camera usually contains a lot of noisy components caused by the characteristics of depth camera and edges are also more distorted by the quality of a source object and illumination condition comparing with edges in RGB texture image. To reduce this distortion, we use noise removing filters, but they are only able to reduce noise components, so that distorted edges of depth map can not be properly recovered. In this paper, we propose an algorithm that can reduce noise components and also enhance the quality of edges of depth map by using edges in RGB texture. Consequently, we can reduce errors in multi-view stereo image synthesis process.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.151-156
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• 2010

This paper is a study on image noise reduction of modified sigma filter by image decomposition using directivity. Conventional sigma filter has been shown to be a good solution both in terms of filtering accuracy and computational complexity. However, the sigma filter does not preserve well small edges especially for high level of additive noise. In this paper, we propose here a new method using a modified sigma filter. In our proposed method the input image is first decomposed in two components that have features of horizontal, vertical and diagonal direction. Then, two components are applied HPF and LPF. By applying a conventional sigma filter separately on each of them, the output image is reconstructed from the filtered components. Added noise is removed and our proposed method preserves the edges from the image. Comparative results from experiments show that the proposed algorithm achieves higher gains, on average, 2.6 dB PSNR than the sigma filter and 0.5 dB PSNR than the modified sigma filter. When relatively high levels of noise added, the proposed algorithm shows better performance than two conventional filters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1216-1223
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• 2006

In many imaging devices, a single image sensor is used, which is covered by a color filter array to filter out the specific color components from light. Since an image acquired from this image sensors have a color components at each pixel, it is needed to be reconstructed to a perfect image. In this paper, a new color interpolation method for the imaging devices having a single image sensor is proposed. The proposed method improves a edge sensing function to obtain satisfactory results in edges of an image, md presents a new inter-channel correlation for improving interpolation performance in smooth region. We have compared our method with several exiting methods, and our experimental results have proved better interpolation performance in comparing with the other results.