• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.268-274
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• 2023

Image mosaicking is one of the basic and important technologies in the field of application using images. The key of image mosaicking is to extract seamlines from a joint image. The method proposed in this paper for image mosaicking is as follows. The feature points of the images to be joined are extracted and the joining form between the two images is identified. A reference position for detection the seamlines were selected according to the joint form, and an image pyramid was created for efficient image processing. The outlines of the image including buildings and roads are extracted from the overlapping area with low resolution, and the seamlines are determined by considering the components of the outlines. Based on this, the seamlines in the high-resolution image was re-searched and finally the seamline for image mosaicking was determined. In addition, in order to minimize color distortion of the image with the determined seamline, a method of improving the quality of the mosaic image by fine correction of the mosaic area was applied. It was confirmed that the quality of the seamline extraction results applying the method proposed was reasonable.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1604-1611
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• 2020

Light field image captured by a microlens array-based camera has many limitations in practical use due to its low spatial resolution and angular resolution. High spatial resolution images can be easily acquired with a single image super-resolution technique that has been studied a lot recently. But there is a problem in that high angular resolution images are distorted in the process of using disparity information inherent among images, and thus it is difficult to obtain a high-quality angular resolution image. In this paper, we propose light field angular super-resolution that extracts an initial feature map using an dilated convolutional neural network in order to effectively extract the view difference information inherent among images and generates target image using a residual neural network. The proposed network showed superior performance in PSNR and subjective image quality compared to existing angular super-resolution networks.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.449-460
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• 2020

Super-resolution is a technique used to reconstruct an image with low-resolution into that of high-resolution. Recently, deep-learning based super resolution has become the mainstream, and applications of these methods are widely used in the remote sensing field. In this paper, we propose a super-resolution method based on the deep back-projection network model to improve the satellite image resolution by the factor of four. In the process, we customized the loss function with the edge loss to result in a more detailed feature of the boundary of each object and to improve the stability of the model training using generative adversarial network based on Wasserstein distance loss. Also, we have applied the detail preserving image down-scaling method to enhance the naturalness of the training output. Finally, by including the modified-residual learning with a panchromatic feature in the final step of the training process. Our proposed method is able to reconstruct fine features and high frequency information. Comparing the results of our method with that of the others, we propose that the super-resolution method improves the sharpness and the clarity of WorldView-3 and KOMPSAT-2 images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1816-1825
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• 2022

In this paper, we propose a new approach for tracking each human in a surveillance camera network with various resolution cameras. When tracking human on multiple non-overlapping cameras, the traditional appearance features are easily affected by various camera viewing conditions. To overcome this limitation, the proposed system utilizes facial information along with appearance information. In general, human images captured by the surveillance camera are often low resolution, so it is necessary to be able to extract useful features even from low-resolution faces to facilitate tracking. In the proposed tracking scheme, texture-based face descriptor is exploited to extract features from detected face after face frontalization. In addition, when the size of the face captured by the surveillance camera is very small, a super-resolution technique that enlarges the face is also exploited. The experimental results on the public benchmark Dana36 dataset show promising performance of the proposed algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1871-1874
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• 2005

The direct write FIB technology has several advantages over contemporary micro-machining technology, including better feature resolution with low lateral scattering and capability of maskless fabrication. Therefore, the application of FIB technology in micro fabrication has become increasingly popular. In recent model of FIB, however the feeding system has been a very coarse resolution of about a few ${\mu}m$. Our research is the development of nano stage of 200mm strokes and 10nm resolutions. Also, this stage should be effectively operating in ultra high vacuum of about $1x10^{-7}$ torr. This paper presents the discussion and results of CAE of the 2 axes stages. we have estimated the stable static and dynamic characteristics for dual servo system. Therefore the 2 axes stages developed and future work are introduced at the end of the paper.

• Journal of Information Display
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• v.8 no.4
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• pp.27-31
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• 2007

In this paper, we present an efficient tiled stereo display system for tangible meeting. For tangible meeting, it is important to provide immersive display with high resolution image to cover up the field of view and provide to the local user the same environment as that of remote site. To achieve these, a high resolution image needs to be transmitted for reconstruction of remote world, and it should be displayed using a tiled display. However, it is hard to transmit high resolution image in real time due to the limit of network bandwidth, and so we receive multiple images and reconstruct a remote world with received images in advance. Then, we update only a specific area where remote user exists by receiving low resolution image in realtime. We synthesize the transmitted image to the existing environmental map of remote world and display it as a stereo image. For this, we developed a new system which supports GPU based real time warping and blending, automatic feature extraction using machine vision technique.

• Smart Structures and Systems
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• v.5 no.4
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• pp.345-355
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• 2009

This article describes the development of a fiber optic accelerometer based on Fiber Bragg Gratings (FBG). The accelerometer utilizes the stiffness of the optical fiber and a lumped mass in the design. Acceleration is measured by the FBG in response to the vibration of the fiber optic mass system. The wavelength shift of FBG is proportional to the change in acceleration, and the gauge factor pertains to the shift in wavelength as a function of acceleration. Low frequency version of the accelerometer was developed for applications in monitoring bridges. The accelerometer was first evaluated in laboratory settings and then employed in a demonstration project for condition assessment of a bridge. Laboratory experiments involved evaluation of the sensitivity and resolution of measurements under a series of low frequency low amplitude conditions. The main feature of this accelerometer is single channel multiplexing capability rendering the system highly practical for application in condition assessment of bridges. This feature of the accelerometer was evaluated by using the system during ambient vibration tests of a bridge. The Frequency Domain Decomposition method was employed to identify the mode shapes and natural frequencies of the bridge. Results were compared with the data acquired from the conventional accelerometers.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.472-477
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• 2004

Miniaturization is the central theme in modern fabrication technology. Many of the components used in modem products are becoming smaller and smaller. The direct write FIB technology has several advantages over contemporary micromachining technology, including better feature resolution with low lateral scattering and capability of mastless fabrication. Therefore, the application of focused ion beam(FIB) technology in micro fabrication has become increasingly popular. In recent model of FIB, however the feeding system has been a very coarse resolution of about a few ${\mu}{\textrm}{m}$. It is not unsuitable to the sputtering and the deposition to make the high-precision structure in micro or macro scale. Our research is the development of nano stage of 200mm strokes and l0nm resolutions. Also, this stage should be effectively operating in ultra high vacuum of about 1$\times$10$^{-5}$ pa. This paper presents the concept of nano stages and the discussion of the material treatment for ultra tush vacuum.

• Proceedings of the Korean Society Of Semiconductor Equipment Technology
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• 2004.05a
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• pp.223-228
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• 2004

Miniaturization is the central theme in modern fabrication technology. Many of the components used in modern products are becoming smaller and smaller. The direct write FIB technology has several advantages over contemporary micromachining technology, including better feature resolution with low lateral scattering and capability of maskless fabrication. Therefore, the application of FIB technology in micro fabrication has become increasingly popular. In recent model of FIB, however the feeding system has been a very coarse resolution of about a few $\mu\;\textrm{m}$. It is not unsuitable to the sputtering and the deposition to make the high-precision structure in micro or macro scale. Our research is the development of nano stage of 200mm strokes and 10nm resolutions. Also, this stage should be effectively operating in ultra high vacuum of about $1\times10^{-7}$ torr. This paper presents the concept of nano stages and the discussion of the material treatment for ultra high vacuum.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.141-144
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• 2001

In this paper, a new algorithm for extracting and recognizing characters from video, without pre-knowledge such as font, color, size of character, is proposed. To improve the recognition rate for videos with complex background at low resolution, continuous frames with identical text region are automatically detected to compose an average frame. Using boundary pixels of a text region as seeds, we apply region filling to remove background from the character Then color clustering is applied to remove remaining backgrounds according to the verification of region filling process. Features such as white run and zero-one transition from the center, are extracted from unknown characters. These feature are compared with a pre-composed character feature set to recognize the characters.