• Journal of Distribution Science
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• v.20 no.3
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• pp.83-93
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• 2022

Purpose: This study aims to investigate the relationship between ESG activities (Environment, Social, Governance) of coffee shops and their brand image, purchase intention. Research design, data and methodology: To test the hypothesis, a survey was conducted for about one month from May to June, 2021, and a total of 311 people responded to the survey, and the responses from 311 copies were used for the analysis. Validity and reliability analysis were performed, and the relationship between latent variables was empirically analyzed using the structural equation modelling. Results: The results of the study are as follows. First, among the ESG activities of coffee shops, the environmental and social sectors had a significant positive (+) effect on the brand image, but the governance aspect showed no significant effect on the brand image. Second, it was found that the symbolic image and the empirical image had a significant positive (+) effect on the purchase intention, but the functional image did not have a significant effect on the purchase intention. Conclusions: The results of this study suggest that as the number of coffee shops and the heated competition are increasing, it is possible to build a differentiated brand image through ESG activities rather than relying on the functions and services of competing products.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.61-70
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• 2023

Image segmentation is a very crucial step in effective digital image processing. In the past decade, several research contributions were given related to this field. However, a general segmentation algorithm suitable for various applications is still challenging. Among several image segmentation approaches, graph-based approach has gained popularity due to its basic ability which reflects global image properties. This paper proposes a methodology to partition the image with its pixel, region and texture along with its intensity. To make segmentation faster in large images, it is processed in parallel among several CPUs. A way to achieve this is to split images into tiles that are independently processed. However, regions overlapping the tile border are split or lost when the minimum size requirements of the segmentation algorithm are not met. Here the contributions are made to segment the image on the basis of its pixel using min-cut/max-flow algorithm along with edge-based segmentation of the image. To segment on the basis of the region using a homogenous optimum cut algorithm with boundary segmentation. On the basis of texture, the object type using spectral partitioning technique is identified which also minimizes the graph cut value.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.953-960
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• 2014

In Shamir's (t,n)-threshold based secret image sharing schemes, there exists a problem that the secret image can be reconstructed when an arbitrary attacker becomes aware of t secret image pieces, or t participants are malicious collusion. It is because that utilizes linear combination polynomial arithmetic operation. In order to overcome the problem, we propose a secret image sharing scheme using matrix decomposition and adversary structure. In the proposed scheme, there is no reconstruction of the secret image even when an arbitrary attacker become aware of t secret image pieces. Also, we utilize a simple matrix decomposition operation in order to improve the security of the secret image. In experiments, we show that performances of embedding capacity and image distortion ratio of the proposed scheme are superior to previous schemes.

• Journal of Korea Multimedia Society
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• v.15 no.5
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• pp.569-576
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• 2012

This paper presents an x-ray medical image panorama system which can overcome the smallness of the images that exist on a source computer during remote medical processing. In the system, after the standard medical image format DICOM is converted to the PC standard image format, a MSR algorithm is used to enhance X-ray images of low quality. Then SURF and Multi-band blending are applied to generate a panoramic image. Also, this paper evaluates the proposed SURF based system through the average gray value error and image quality criterion with X-ray image data by comparing with a SIFT based system. The results show that the proposed system is superior to SIFT based system in image quality.

• Korean Management Science Review
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• v.27 no.2
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• pp.97-108
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• 2010

Previous studies have shown that country image affects consumers' valuation of products. Based on a literature review this paper identifies five dimensions (economic, political, relational, people and cultural image) and purifies them with Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). The data was gathered by using a structured questionnaire from 252 Korean consumers. Among the five dimensions of country image, this paper derives the three factors of country image for four countries (The United States, Japan, Australia, and China) - economic, relational, and cultural image. Then it examines the impacts of the three dimensions of country image on consumers' purchase intention of two industry types : industrial products vs. agricultural products. The result shows there is no difference between both of the two types in the impacts of country image on purchase intention. This implies that for managing the country image it not necessary to develop a communication strategy which is differentiated by industry types.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.660-664
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• 2006

A novel quantified method based on requirement analysis of image quality to improve display image quality was proposed. Nowadays, the image quality was limited by the poor understanding of the image quality requirement, which led to the critical factors of image quality could not be controlled during display development. Our method was set up to resolve this problem by clarifying the relationship between the image quality level and the effect factors in image processing. Moreover, the subjective factors were eliminated extremely by the image quality quantification. The method was applied in the RPTV development life cycle and its efficiency was demonstrated.

• Current Optics and Photonics
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• v.1 no.4
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• pp.336-343
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• 2017

A wide field-of-view (FOV) image contains more visual information than a conventional image. This study proposes a new type of hyperbolic mirror for wide FOV image acquisition. The proposed mirror consists of a hyperbolic cylindrical section and a bowl-shaped hyperbolic omnidirectional section. Using an imaging system with this mirror, it is possible to achieve a $213.8^{\circ}$ horizontal and a $126.94^{\circ}$ vertical maximum FOV. Parameters of each section of the mirror are designed to be continuous at the junction of the two parts, and the resultant image is seamless. The image-acquisition model is obtained using ray-tracing optics. To rectify the geometrical distortion of the original image due to the mirror, an image-restoration algorithm based on conformal projection is presented in this study. The performance of the proposed imaging system with the hyperbolic mirror and its image-restoration algorithm are verified by experiments.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.1-12
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• 2016

In this paper, we propose a very efficient reversible data hiding algorithm using spatial locality and the surface characteristics of image. Spacial locality and a variety of surface characteristics are present in natural images. So, it is possible to precisely predict the pixel value using the locality and surface characteristics of image. Therefore, the frequency is increased significantly at the peak point of the difference histogram using the precisely predicted pixel values. Thus, it is possible to increase the amount of data to be embedded in image using the spatial locality and surface characteristics of image. By using the proposed reversible data hiding algorithm, visually high quality stego-image can be generated, the embedded data and the original cover image can be extracted without distortion from the stego-image, and the embedding data are much greater than that of the previous algorithm. The experimental results show the superiority of the proposed algorithm.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.232-239
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• 2023

Aiming at the poor compression quality of traditional image compression coding (ICC) algorithm, a multi-description ICC algorithm based on depth learning is put forward in this study. In this study, first an image compression algorithm was designed based on multi-description coding theory. Image compression samples were collected, and the measurement matrix was calculated. Then, it processed the multi-description ICC sample set by using the convolutional self-coding neural system in depth learning. Compressing the wavelet coefficients after coding and synthesizing the multi-description image band sparse matrix obtained the multi-description ICC sequence. Averaging the multi-description image coding data in accordance with the effective single point's position could finally realize the compression coding of multi-description images. According to experimental results, the designed algorithm consumes less time for image compression, and exhibits better image compression quality and better image reconstruction effect.

• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.32-40
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• 2022

Underwater optical images face various limitations that degrade the image quality compared with optical images taken in our atmosphere. Attenuation according to the wavelength of light and reflection by very small floating objects cause low contrast, blurry clarity, and color degradation in underwater images. We constructed an image data of the Korean sea and enhanced it by learning the characteristics of underwater images using the deep learning techniques of CycleGAN (cycle-consistent adversarial network), UGAN (underwater GAN), FUnIE-GAN (fast underwater image enhancement GAN). In addition, the underwater optical image was enhanced using the image processing technique of Image Fusion. For a quantitative performance comparison, UIQM (underwater image quality measure), which evaluates the performance of the enhancement in terms of colorfulness, sharpness, and contrast, and UCIQE (underwater color image quality evaluation), which evaluates the performance in terms of chroma, luminance, and saturation were calculated. For 100 underwater images taken in Korean seas, the average UIQMs of CycleGAN, UGAN, and FUnIE-GAN were 3.91, 3.42, and 2.66, respectively, and the average UCIQEs were measured to be 29.9, 26.77, and 22.88, respectively. The average UIQM and UCIQE of Image Fusion were 3.63 and 23.59, respectively. CycleGAN and UGAN qualitatively and quantitatively improved the image quality in various underwater environments, and FUnIE-GAN had performance differences depending on the underwater environment. Image Fusion showed good performance in terms of color correction and sharpness enhancement. It is expected that this method can be used for monitoring underwater works and the autonomous operation of unmanned vehicles by improving the visibility of underwater situations more accurately.