• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.337-339
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• 2005

The demand for a real-time image surveillance system using network camera server is increasing as the network infra has been grown and digital video compression techniques have been developed. The image surveillance system using network camera server has several merits compared to existing real-time image surveillance system using CCTV. It would be more convenient if wireless realtime image transmission were possible. In this paper, a bluetooth module is designed and implemented for a real-time image surveillance system to send and receive informations wirelessly. It may simplify the system development procedures and increase the productivity by low power consumption, low cost, and simple wireless installation. A scatter-net formation is proposed using dynamic and distributed algorithm so that the network connection is reliable.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.25-28
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• 2001

In this paper we implement moving picture transfer system using bluetooth Development Kit (DK). To reduce the size of the image data, we use M-JPEG compression. We use bluetooth Synchronous Connection-Oriented (SCO) link to transfer voice data. Server receive image data from camera and compress the image data in M-JPEG format, and then transmit the image data to client using bluetooth Asynchronous connection-less (ACL) link. Client receive image data from bluetooth ACL link and decode the compressed image and then display the image to screen. Sever and Client can transmit and receive voice data simultaneously using bluetooth SCO link. In this paper bluetooth HCI commands and events generated by host controller to return the results of HCI commands are explained and the flow of bluetooth connection procedure is presented.

• Asian Journal for Public Opinion Research
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• v.8 no.2
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• pp.126-143
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• 2020

Since 2008, strategic partnerships have been established between China and Korea. From 2009 to 2019, the bilateral relationship kept a generally stable rate of development with conflicts and uncertainties. It is necessary to study national image construction in the respective mainstream media of the two countries. The present study analyzed Korea-related reports (N = 744) in the People's Daily from 2009 to 2019, aiming to examine the Korean national image framing under Fairclough's three-dimensional Critical Discourse Analysis (CDA) framework: "whatness," "how," and "whyness." The results shed light on what the Korean national image in the People's Daily was and how and why it was framed in that way. This study provided some implications for readers to further recognize the role that media play in constructing a particular image of one country and a frame for researchers to study foreign national image framing in one of China's mainstream newspapers.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.969-970
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• 2006

This paper develops a recognition system of assembly parts using a hardware independent image module. Using a shared memory, the image module consists of the image acquiring process and the image processing process. We preprocess an acquisition image from the module, approximate the image edges to an ellipse, and then recognize an assembly part by matching the ellipse to a model base one.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1998.05a
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• pp.351-358
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• 1998

This paper deals with the underwater image transmission system which includes in AUV(Autonomous Underwater Vehicle) Project(that is VORAM(Vehicle for Ocean Research And Monitoring)), developed by KIMM for survey and investigation of a sea-bed through transmitting the underwater image to the mother ship. The system presented in this paper consists of a transducer which has a 136KHz center frequency and it's 10KHz bandwidth, pre-amplifier, $\pi$/4 QPSK(Quadreature Phase Shift Keying) modulation/demodulation method, image compressing method using JPEG technique and modified Stop & protocol. The experimental results of the system is verified to a high performance with 9600 bps for transmitting the underwater image through the basin test. The results of test are also verified which allows to desirable transmission performance compared with the existing developed system and the possibility to put the practical use of survey and investigation. And, the viterbi coding and adaptive equalizer for cancelling the multipath effect are developing for more effective image transmission system. Also, these technique will very effectively adapt to realtime image transmission system.

• Journal of Sensor Science and Technology
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• v.30 no.5
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• pp.286-289
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• 2021

Image classification is one of the fundamental applications of computer vision. It enables a system to identify an object in an image. Recently, image classification applications have broadened their scope from computer applications to edge devices. The convolutional neural network (CNN) is the main class of deep learning neural networks that are widely used in computer tasks, and it delivers high accuracy. However, CNN algorithms use a large number of parameters and incur high computational costs, which hinder their implementation in edge hardware devices. To address this issue, this paper proposes a lightweight image classifier that provides good accuracy while using fewer parameters. The proposed image classifier diverts the input into three paths and utilizes different scales of receptive fields to extract more feature maps while using fewer parameters at the time of training. This results in the development of a model of small size. This model is tested on the CIFAR-10 dataset and achieves an accuracy of 90% using .26M parameters. This is better than the state-of-the-art models, and it can be implemented on edge devices.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.195-203
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• 2022

Noise generated during image acquisition and transmission can negatively impact the results of image processing applications, and noise removal is typically a part of image preprocessing. Denoising techniques combined with nonlocal techniques have received significant attention in recent years, owing to the development of sophisticated hardware and image processing algorithms, much attention has been paid to; however, this approach is relatively poor for edge preservation of fine image details. To address this limitation, the current study combined a steering kernel technique with adaptive masks that can adjust the size according to the noise intensity of an image. The algorithm sets the steering weight based on a similarity comparison, allowing it to respond to edge components more effectively. The proposed algorithm was compared with existing denoising algorithms using quantitative evaluation and enlarged images. The proposed algorithm exhibited good general denoising performance and better performance in edge area processing than existing non-local techniques.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.33-45
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• 2023

This paper proposes an algorithm that automatically converts images into Pipo, painting images using OpenCV-based image processing technology. The existing "purity," "palm," "puzzling," and "painting," or Pipo, painting image production method relies on manual work, so customized production has the disadvantage of coming with a high price and a long production period. To resolve this problem, using the OpenCV library, we developed a technique that automatically converts an image into a Pipo painting image by designing a module that changes an image, like a picture; draws a line based on a sector boundary; and writes sector numbers inside the line. Through this, it is expected that the production cost of customized Pipo painting images will be lowered and that the production period will be shortened.

• The Korean Journal of Emergency Medical Services
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• v.27 no.1
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• pp.71-77
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• 2023

Purpose: This study aimed to analyze the research trends on the image of emergency medical technicians (EMTs) in studies published in Korean journals. Methods: Electronic databases were searched, including RISS, KMbase, and KCI. Eight studies from 21 references screened were included in the analysis. Results: The number of studies related to the image of EMTs is severely lacking. The research methods and participants are limited to questionnaire surveys and EMT students, respectively. In addition, most of the studies used modified tools developed for image measurement of other occupations. Conclusion: Image research for EMTs should include various methods and participants. Standardized measurement tool development and image-related research should be steadily conducted.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.112-115
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• 2022

The process of deep learning usually needs to deal with massive data which has greatly limited the development of deep learning technologies today. Convolutional Neural Network (CNN) structure is often used to solve image classification problems. However, a large number of images may be required in order to train an image in CNN, which is a heavy burden for existing computer systems to handle. If the image data can be compressed under the premise that the computer hardware system remains unchanged, it is possible to train more datasets in deep learning. However, image compression usually adopts the form of lossy compression, which will lose part of the image information. If the lost information is key information, it may affect learning performance. In this paper, we will analyze the effect of image compression on deep learning performance on CNN-based cat and dog classification. Through the experiment results, we conclude that the compression of images does not have a significant impact on the accuracy of deep learning.