• IEIE Transactions on Smart Processing and Computing
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• v.4 no.5
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• pp.311-317
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• 2015

The aim of this study is to develop a 3D registration algorithm for positron emission tomography/computed tomography (PET/CT) and magnetic resonance (MR) images acquired from independent PET/CT and MR imaging systems. Combined PET/CT images provide anatomic and functional information, and MR images have high resolution for soft tissue. With the registration technique, the strengths of each modality image can be combined to achieve higher performance in diagnosis and radiotherapy planning. The proposed method consists of two stages: normalized mutual information (NMI)-based global matching and independent component analysis (ICA)-based refinement. In global matching, the field of view of the CT and MR images are adjusted to the same size in the preprocessing step. Then, the target image is geometrically transformed, and the similarities between the two images are measured with NMI. The optimization step updates the transformation parameters to efficiently find the best matched parameter set. In the refinement stage, ICA planes from the windowed image slices are extracted and the similarity between the images is measured to determine the transformation parameters of the control points. B-spline. based freeform deformation is performed for the geometric transformation. The results show good agreement between PET/CT and MR images.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1934-1935
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• 2011

In order for a service robot to perform several tasks, basically autonomous navigation technique such as localization, mapping, and path planning is required. The localization (estimation robot's pose) is fundamental ability for service robot to navigate autonomously. In this paper, we propose a new system for point pattern matching based visual global localization using spot lightings in ceiling. The proposed algorithm us suitable for system that demands high accuracy and fast update rate such a guide robot in the exhibition. A single camera looking upward direction (called ceiling vision system) is mounted on the head of the mobile robot and image features such as lightings are detected and tracked through the image sequence. For detecting more spot lightings, we choose wide FOV lens, and inevitably there is serious image distortion. But by applying correction calculation only for the position of spot lightings not whole image pixels, we can decrease the processing time. And then using point pattern matching and least square estimation, finally we can get the precise position and orientation of the mobile robot. Experimental results demonstrate the accuracy and update rate of the proposed algorithm in real environments.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.368-373
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• 2007

In recent year s there have been increasing interests in real-time object tracking with image information. This dissertation presents a real-time object tracking method through the object recognition based on neural networks that have robust characteristics under various illuminations. This dissertation proposes a global search and a local search method to track the object in real-time. The global search recognizes a target object among the candidate objects through the entire image search, and the local search recognizes and track only the target object through the block search. This dissertation uses the object color and feature information to achieve fast object recognition. The experiment result shows the usefulness of the proposed method is verified.

• Journal of the Korea Fashion and Costume Design Association
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• v.16 no.4
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• pp.37-47
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• 2014

Recently, the Korean wave has caused many foreign nations to pay attention to various fields including Korean culture, arts, fashion and beauty. Korean images so far were mainly discussed in terms of aesthetics, and there is lack of efforts to visually shape Korean images. On the contrary, Oriental images focused around Japan and China have greater global influence and better globalized fashion styles compared to Korea. Therefore, it is necessary to suggest a globalized proposal of Korean fashion styling which reflects original and unique aesthetic characteristics of Korea that can be accepted by the global market. In this study, the concept and types of fashion styling and stylists were examined, as well as the definition of Korean image and types and characteristics of Korean images shown on fashion magazines. Also, after collecting photographs having Korean images that were included in the editorial fashion styling of Vogue Korea, their characteristics were analyzed. The results of interviews with professional fashion stylists were summarized to propose an editorial fashion styling with Korean image for overseas consumers who long for and wish to imitate Korean fashion styling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2287-2312
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• 2018

Extracting key visual information from images containing natural scene is a challenging task and an important step for the visually impaired to recognize information based on tactile graphics. In this study, a novel method is proposed for extracting salient regions based on global contrast enhancement and saliency cuts in order to improve the process of recognizing images for the visually impaired. To accomplish this, an image enhancement technique is applied to natural scene images, and a saliency map is acquired to measure the color contrast of homogeneous regions against other areas of the image. The saliency maps also help automatic salient region extraction, referred to as saliency cuts, and assist in obtaining a binary mask of high quality. Finally, outer boundaries and inner edges are detected in images with natural scene to identify edges that are visually significant. Experimental results indicate that the method we propose in this paper extracts salient objects effectively and achieves remarkable performance compared to conventional methods. Our method offers benefits in extracting salient objects and generating simple but important edges from images containing natural scene and for providing information to the visually impaired.

• International journal of advanced smart convergence
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• v.8 no.1
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• pp.153-158
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• 2019

Language and letter are represented by a combination of its signifier and signified. All symblos are commonly calling direct attention to people who are living in the physical world. However, in cyberspace, the image takes control once inhabited by the language. Cyberspace with anonymity and deoent physical nature has something with physical laws. In this space the statue transcends the imaginary realm. Ideology gives a greater connotation by giving a series of regulation to images floating in cyberspace. Even if various media have the same image, the meaning of the image changes depending on which ideology is used. The impact of this on the public is great. In this study, I discuss the ideology in cyberspace where is supposedly wide open to who visits and spreads all the thoughts without suppression and the human body. The main ideas would be who owns the ideology and what does it want to control and how the people would react to the ideology. This paper would eventually head the prototype that visualizes above ideas. Though the interactive media it will also show the subject in the real world is accept the images floating in the cyberspace without any doubts.

• Journal of Multimedia Information System
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• v.9 no.2
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• pp.87-92
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• 2022

In this study, we aimed to illustrate that the thresholding method gives different results when tested on the original and the refined histograms. We use the global thresholding method, the well-known image segmentation method for separating objects and background from the image, and the refined histogram is created by the neighborhood distinction metric. If the original histogram of an image has some large bins which occupy the most density of whole intensity distribution, it is a problem for global methods such as segmentation and contrast enhancement. We refined the histogram to overcome the big bin problem in which sub-bins are created from big bins based on distinction metric. We suggest the refined histogram for preprocessing of thresholding in order to reduce the big bin problem. In the test, we use Otsu and median-based thresholding techniques and experimental results prove that their results on the refined histograms are more effective compared with the original ones.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.406-412
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• 2022

Scene classification of very high-resolution (VHR) imagery can attribute semantics to land cover in a variety of domains. Real-world application requirements have not been addressed by conventional techniques for remote sensing image classification. Recent research has demonstrated that deep convolutional neural networks (CNNs) are effective at extracting features due to their strong feature extraction capabilities. In order to improve classification performance, these approaches rely primarily on semantic information. Since the abstract and global semantic information makes it difficult for the network to correctly classify scene images with similar structures and high interclass similarity, it achieves a low classification accuracy. We propose a VHR remote sensing image classification model that uses extracts the global feature from the original VHR image using an EfficientNet-V2L CNN pre-trained to detect similar classes. The image is then classified using a multilayer perceptron (MLP). This method was evaluated using two benchmark remote sensing datasets: the 21-class UC Merced, and the 38-class PatternNet. As compared to other state-of-the-art models, the proposed model significantly improves performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.349-354
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• 2023

As the population interested in interior design has been increasing, the global interior market has grown significantly. Global interior companies are developing and providing simulation services for various interior elements. Although wallpaper design is the most important interior element, existing wallpaper design simulation services are difficult to use due to drawbacks such as differences between expected and actual results, long simulation time, and the need for professional skills. We proposed a wallpaper image transformation method for interior design using cycle generative adversarial networks (GAN). The proposed method demonstrates that users can simulate wallpaper design within a short period of time based on interior image data using various types of wallpaper.

• Journal of Contemporary Eastern Asia
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• v.22 no.2
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• pp.18-38
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• 2023

This paper examines the Chinese government's response to four epidemic crises, including COVID-19, and analyzes the similarities and differences in these responses. It argues that while the Chinese government learned from previous epidemics and improved its handling of subsequent outbreaks, a significant variation occurred during the COVID-19 pandemic, which had a detrimental impact globally. Existing scholarly research on China's epidemic responses has often been limited in scope, focusing on individual crises and neglecting the central-local government relationship in crisis decision-making. By adopting a comprehensive approach, this paper delves into the nuanced dynamics of China's responses to these epidemics. It highlights the variations in responses, attributing them to the Chinese government's fear of undermined legitimacy and its consideration of its international image. The government's recognition of the importance of public perception and trust, both domestically and globally, has shaped its crisis management strategies. Through a detailed analysis of these factors, this paper contributes to a deeper understanding of the variations observed in China's epidemic responses. It emphasizes the significance of the central-local government relationship and the government's international image in determining its actions during epidemics. Recognizing these factors can provide policymakers and researchers with insights to shape future epidemic response strategies and foster effective global health governance.