• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.51-59
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• 2024

In this work, we focused on reducing the amount of image data to be sent by extracting and progressively sending prominent image features to high-performance computing systems taking into consideration the right amount of image data required by object identification application. We demonstrate that with our technique called Progressive Object Detection over a Lossless Network using Fragmented DCT Coefficients (Proficient), object identification applications can detect objects with at least 70% combined confidence level by using less than half of the image data.

• Journal of Environmental Science International
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• v.14 no.10
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• pp.905-910
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• 2005

The purpose of this study is the comparative analysis of Susan citizens' images of Eulsook-do as a coastal tourism destination before and after the construction of a road bridge across the Nakdong estuary in order to analyze local people's changes in leisure patterns. Analysis of the images of a pre-construction Eulsook-do that people aged both 40 and less and 50 and more had on five dimensions showed values higher than zero(0) that suggests neutral image, while their images of a post-construction Eulsook-do showed the shrinking size of pentagon on all five dimensions: ET(Entertainment), CA(Culture & Art), EE(Environment & Ecology), RC(Recreation) and LP(Leports) dimensions. Its pre- and post- construction image analysis conducted 20 years after it came to be built finds that the road bridge construction has led to the ecological, environmental disruption of the coast and the lower Nakdong river, having negative influence on the images of Eulsook-so.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.136-142
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• 2024

Haze is a very common phenomenon that degrades or reduces the visibility. It causes various problems where high quality images are required such as traffic and security monitoring. So haze removal from images receives great attention for clear vision. Due to its huge impact, significant advances have been achieved but the task yet remains a challenging one. Recently, different types of deep generative adversarial networks (GAN) are applied to suppress the noise and improve the dehazing performance. But it is unclear how these algorithms would perform on hazy images acquired "in the wild" and how we could gauge the progress in the field. This paper aims to bridge this gap. We present a comprehensive study and experimental evaluation on diverse GAN models in single image dehazing through benchmark datasets.

• Progress in Medical Physics
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• v.23 no.4
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• pp.292-302
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• 2012

The patient dose in advanced radiotherapy techniques is an important issue. These methods should be evaluated to reduce the dose in diagnostic imaging for radiotherapy. Especially, the Computed Tomography in radiotherapy has been used widely; hence the CT was evaluated for dose and image in this study. The evaluations for dose and image were done in equal condition due to compare the dose and image simultaneously. Furthermore, the possibility of dose and image evaluations by using the Monte Carlo simulation MCNPX was confirmed. We made the iterative reconstruction for low dose CT image to elevate image quality with Maximum Likelihood Expectation Maximization; MLEM. The system we developed is expected to be used not only to reduce the patient dose in radiotherapy, also to evaluate the overall factors of image modalities in industrial research.

• The Research Journal of the Costume Culture
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• v.21 no.6
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• pp.907-920
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• 2013

The purpose of this study was to examine interactive effect of wedding makeup, head dress, and perceiver's culture on bride's image perception. Image analysis was carried out by 10 photos which was designed for brides in their twenties with different makeup and head dress. Subjects were female university students in Seoul, Korea and 100 black female university students in Delaware, U.S. The result of study was as follows. Image perception by bride's makeup and head dress was classified as five dimensions: 'distinctive', 'tidy', 'elegant', 'soft', and 'beautiful'. There was a significant difference in image perception from culture and head dress. The result of interactive effect due to culture and makeup showed that Korean students perceived pink makeup as close to more elegant image, and American students felt orange makeup. We can know through above contents that there was significant difference in image perception by makeup and head dress between Korean and American students. Also, American students in general evaluated the photos (stimulus) presented positively compared to Korean students. This can be interpreted as a meaning that the degree to perceive each photos of American students was lower than Korean students.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.283-289
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• 2023

AI is bringing about drastic changes not only in the aspect of technologies but also in society and culture. Medical AI based on deep learning have developed rapidly. Especially, the field of medical image analysis has been proven that AI can identify the characteristics of medical images more accurately and quickly than clinicians. Evaluating the latest results of the AI-based medical image processing is important for the implication for the development direction of medical AI. In this paper, we analyze and evaluate the latest trends in AI-based medical image analysis, which is showing great achievements in the field of medical AI in the healthcare industry. We analyze deep learning models for medical image analysis and AI-based medical image segmentation for quantitative analysis. Also, we evaluate the future development direction in terms of marketability as well as the size and characteristics of the medical AI market and the restrictions to market growth. For evaluating the latest trend in the deep learning-based medical image processing, we analyze the latest research results on the deep learning-based medical image processing and data of medical AI market. The analyzed trends provide the overall views and implication for the developing deep learning in the medical fields.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.85-94
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• 2023

Image halftoning is a technique for varying grayscale images into two-tone binary images. Unfortunately, the static representation of an image-half toning, wherever each pixel intensity is combined by its local neighbors only, causes missing subjective problem. Also, the existing noise causes an instability criterion. In this paper an image half-toning is represented as a dynamical system for recognizing the global representation. Also, noise is reduced based on a probabilistic model. Since image half-toning is considered as 2-D matrix with a full connected pass, this structure is recognized by the dynamical system of Cellular Neural Networks (CNNs) which is defined by its template. Bayesian Rough Sets is used in exploiting the ideal CNNs construction that synthesis its dynamic. Also, Bayesian rough sets contribute to enhance the quality of the halftone image by removing noise and discovering the effective parameters in the CNNs template. The novelty of this method lies in finding a probabilistic based technique to discover the term of CNNs template and define new learning rules for CNNs internal work. A numerical experiment is conducted on image half-toning corrupted by Gaussian noise.

• 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 Distribution Science
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• v.15 no.3
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• pp.49-60
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• 2017

Purpose - The aims of this study are follows. We investigated to find out how country image and brand image affect the consumer perceived value, consumer attitude, and purchase intention of foreign infant foods in China. Especially, we focused on investigate for the moderating role of consumer knowledge between national image, brand image and consumer perceived value of foreign infant foods in China. Research design, data, and methodology - This study analyzed the effect of national image and brand image on purchase intention through consumer perceived value and consumer attitude. This study collected data for empirical analysis of Chinese consumers who have been purchase experience infant foods in China. 256 copies of questionnaire data were used for substantial analysis. Before testing the hypothesis, factor analysis was conducted to test the construct validity of measurement items. Hypotheses about effects between variables were verified using structural equation modeling analysis and hierarchical regression analysis. Results - First, the country image had a positive effect on consumer perceived value of foreign infant foods. Second, the brand image had a positive effect on consumer perceived value of foreign infant foods. Third, the consumer perceived value had a positive effect on consumer attitude. Fourth, the consumer attitude had a positive effect on purchase intention. Fifth, the consumer knowledge was moderating roles between brand image and consumer perceived value of foreign infant foods. However, the consumer knowledge did not effect of moderating between country image and perceived value of consumers. Conclusions - First, the impact of country image and brand image on consumer perceived value of foreign infant foods in China can be seen as a universal psychology of consumers who trust pure foreign products such as high quality, technology, etc. Second, consumer perceived value of foreign infant foods has a positive effect on consumer attitude, and this attitude is leading to purchase intention. Third, the consumer knowledge between brand image and perceived value acts as a moderating variable. It means that the consumer's knowledge can shape the perception of the brand image more strongly.

• Journal of Korea Trade
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• v.27 no.1
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• pp.42-59
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• 2023

Purpose - As a leading source of foreign exchange and investment, tourism has grown in importance as a component of international trade. Accordingly, in recent decades much attention has been directed toward attracting foreign tourists and, in turn, positively affecting the recommendation intentions of foreign tourists. Despite such interests, there remains a dearth of empirical research on this issue. Moreover, prior research has focused primarily on the simple main effect of a certain factor on recommendation intentions. Therefore, the present study aims to (1) investigate the effect of overall satisfaction on the recommendation intentions of foreign tourists, and (2) examine the potential moderating effects of personal factors (i.e., age and destination image) on the association between overall satisfaction and recommendation intention. Design/methodology - Using a moderated moderation analysis of the data drawn from the 2018 International Visitor Survey conducted by the Korea Tourism Organization, this study proposes the three-way interaction effects of overall satisfaction, age, and destination image on recommendation intention. Findings - The findings of the study indicate that overall satisfaction is positively associated with recommendation intention and this relationship becomes stronger among younger tourists. The findings further indicate that the moderating effect of age on the relationship between overall satisfaction and recommendation intention depends on changes in the image of the destination. Specifically, the destination image exerts a positive moderating impact on the influence of age that moderates the overall satisfaction and recommendation intention relationship. Originality/value - Considering that the tourism economy has been severely affected by the current COVID-19 pandemic, this study contributes to a more accurate understanding of the factors affecting the recommendation intention, especially in times of crisis.