• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1417-1424
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• 2018

In order to improve the performance of image classifications using Convolutional Neural Networks (CNN), applying a category hierarchy to the classification can be a useful idea. However, the visual separation of object categories is very different according to the upper and lower category levels and highly uneven in image classifications. Therefore, it is doubtable whether the use of category hierarchies for classification is effective in CNN. In this paper, we have clarified whether the image classification using category hierarchies improves classification performance, and found at which level of hierarchy classification is more effective. For experiments we divided the image classification task according to the upper and lower category levels and assigned image data to each CNN model. We identified and compared the results of three classification models and analyzed them. Through the experiments, we could confirm that classification effectiveness was not improved by reduction of number of categories in a classification model. And we found that only with the re-training method in the last network layer, the performance of lower category classification was not improved although that of higher category classification was improved.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.719-722
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• 2019

Gamma-ray images generally suffer from a lot of noise because of low photon detection in the gamma camera system. The purpose of this study is to improve the image quality in gamma-ray images using a gamma camera system with a fast nonlocal means (FNLM) noise reduction algorithm with an acceleration function. The designed FNLM algorithm is based on local region considerations, including the Euclidean distance in the gamma-ray image and use of the encoded information. To evaluate the noise characteristics, the normalized noise power spectrum (NNPS), contrast-to-noise ratio (CNR), and coefficient of variation (COV) were used. According to the NNPS result, the lowest values can be obtained using the FNLM noise reduction algorithm. In addition, when the conventional methods and the FNLM noise reduction algorithm were compared, the average CNR and COV using the proposed algorithm were approximately 2.23 and 7.95 times better than those of the noisy image, respectively. In particular, the image-processing time of the FNLM noise reduction algorithm can achieve the fastest time compared with conventional noise reduction methods. The results of the image qualities related to noise characteristics demonstrated the superiority of the proposed FNLM noise reduction algorithm in a gamma camera system.

• Journal of Space Technology and Applications
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• v.1 no.1
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• pp.41-48
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• 2021

In this paper, we will discuss techniques that can increase the resolution by 1.4 times without distortion or performance degradation of the original image, using diagonal information of the image. The applied method is to use the image information of 4 adjacent points without actual rotating the image by 45 degrees and enlarge and rearrange it according to the characteristics of the camera, so that the same physical concept as the actual 45 degrees can be applied. This is a concrete realization method that can improve the resolution by 1.4 times without deterioration of performance and a demonstration of this result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.211-230
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• 2022

In image segmentation, for the condition that objects (targets) and background in an image are intertwined or their common boundaries are vague as well as their textures are similar, and the targets in images are greatly variable, the deep learning might be difficult to use. Hence, a new method based on graph theory and guided feathering is proposed. First, it uses a guided feathering algorithm to initially separate the objects from background roughly, then, the image is separated into two different images: foreground image and background image, subsequently, the two images are segmented accurately by using the improved graph-based algorithm respectively, and finally, the two segmented images are merged together as the final segmentation result. For the graph-based new algorithm, it is improved based on MST in three main aspects: (1) the differences between the functions of intra-regional and inter-regional; (2) the function of edge weight; and (3) re-merge mechanism after segmentation in graph mapping. Compared to the traditional algorithms such as region merging, ordinary MST and thresholding, the studied algorithm has the better segmentation accuracy and effect, therefore it has the significant superiority.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.59-64
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• 2023

With the recent development of IT technology, medical image processing technology is also widely used in the dental field, and the treatment effect is enhanced by using 3D data such as CT. In this paper, open source libraries such as ITK and VTK are introduced to develop dental medical image processing software, and how to use them to develop dental medical image processing software centering on 3D CBCT. In ITK, basic algorithms for medical image processing are implemented, so the image processing pipeline can be quickly implemented, and the desired algorithm can be easily implemented as a filter by the developer. The developed algorithm is linked with VTK to implement the visualization function. The developed SW can be used for dental diagnosis and treatment that overcomes the limitations of 2D images..

• Annual Conference of KIPS
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• 2021.11a
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• pp.655-658
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• 2021

The purpose of multimodal medical image fusion (MMIF) is to integrate images of different modes with different details into a result image with rich information, which is convenient for doctors to accurately diagnose and treat the diseased tissues of patients. Encouraged by this purpose, this paper proposes a novel method based on a two-scale decomposer and detail preservation model. The first step is to use the two-scale decomposer to decompose the source image into the energy layers and structure layers, which have the characteristic of detail preservation. And then, structure tensor operator and max-abs are combined to fuse the structure layers. The detail preservation model is proposed for the fusion of the energy layers, which greatly improves the image performance. The fused image is achieved by summing up the two fused sub-images obtained by the above fusion rules. Experiments demonstrate that the proposed method has superior performance compared with the state-of-the-art fusion methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2483-2504
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• 2023

Most existing low-light enhancement algorithms either use a large number of training parameters or lack generalization to real-world scenarios. This paper presents a novel lightweight and robust pixel-wise polynomial approximation-based deep network for low-light image enhancement. For mapping the low-light image to the enhanced image, pixel-wise higher-order polynomials are employed. A deep convolution network is used to estimate the coefficients of these higher-order polynomials. The proposed network uses multiple branches to estimate pixel values based on different receptive fields. With a smaller receptive field, the first branch enhanced local features, the second and third branches focused on medium-level features, and the last branch enhanced global features. The low-light image is downsampled by the factor of 2b-1 (b is the branch number) and fed as input to each branch. After combining the outputs of each branch, the final enhanced image is obtained. A comprehensive evaluation of our proposed network on six publicly available no-reference test datasets shows that it outperforms state-of-the-art methods on both quantitative and qualitative measures.

• Korea Trade Review
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• v.45 no.1
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• pp.301-319
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• 2020

This study aims to explore the positive impact of Korean drama watching satisfaction on purchase intention for Korean products by considering the mediating roles of social distance to Korea, national image of Korea, and Korean product image. This study identified that Korean drama reduced the social distance to Korea while increasing the positive image of Koreas and Korean products. However, the reduced social distance was not positively associated with Korean product image and Korean product purchase intention. This implies that Korean dramas directly affect Korean product purchase intension and indirectly affect Korean national image and product image. This study supplies guidance to international marketers who aims to enter the Myanmar market. To use the Korean wave as a Korean product marketing tool, marketing strategies need to cover Korean culture-relevant materials such as cultural background, cultural characteristics, exposed products, and so on.

• Imaging Science in Dentistry
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• v.54 no.1
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• pp.57-62
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• 2024

Purpose: This report presents a unique case featuring real, ghost, and pseudo-ghost images on the panoramic radiograph of a patient wearing earrings. It also explains the formation of these images in an easy-to-understand manner. Materials and Methods: One real image and two ghost images appeared on each side of a panoramic radiograph of a patient wearing earrings on both sides. Of the two ghost images on each side, one was considered a typical ghost image and the other was considered a ghost-like real image (pseudo-ghost image). The formation zones of the real, double, and ghost images were examined based on the path and angles of the X-ray beam from the Planmeca ProMax. To simulate the pseudo-ghost and typical ghost images on panoramic radiography, a radiopaque marker was affixed to the right mandibular condyle of a dry mandible, and the position of the mandible was adjusted accordingly. Results: The center of rotation of the Planmeca ProMax extended beyond the jaw area, and the area of double image formation also reached beyond the jaw. The radiopaque-marked mandibular condyle, situated in the outwardly extending area of double image formation, exhibited triple images consisting of real, double (pseudo-ghost), and ghost images. These findings helped to explain the image formation associated with the patient's earrings observed in the panoramic radiograph. Conclusion: Dentists must understand the characteristics and principles of the panoramic equipment they use and apply this understanding to taking and interpreting panoramic radiographs.

• Journal of the Korean Home Economics Association
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• v.50 no.6
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• pp.33-42
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• 2012

Today, many fashion companies use brand extension and it is especially important to conduct brand extension that coincides with consumer self-image, and maintains brand loyalty in order to succeed. The purpose of this study is to investigate the effect of congruency of parent brand image with self-image, brand loyalty, and brand involvement on the attitude towards extended product in fashion brand extension. A survey questionnaire was used to collect information from 170 female college students, and collected data were subjected to descriptive analysis, factor analysis, and regression analysis. Results showed that the congruency of parent brand image with self-image had a positive effect on the attitude towards extended product in fashion brand extension, with a positive mediating effect of brand loyalty, and a negative mediating effect of brand involvement. Also, the congruency of parent brand image with self-image and brand loyalty of the parent brand had a positive effect on the attitude towards the extended product, whereas brand involvement had a negative mediating effect on the attitude towards the extended product in fashion brand extension. The results of this study provide some useful suggestions to marketers in fashion industry: marketers should consider some psychological aspects of consumers such as congruency of parent brand image with self-image, brand loyalty, and brand involvement when conducting brand extension.