• Journal of Korean Society for Quality Management
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• v.51 no.1
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• pp.119-129
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• 2023

Purpose: This study proposes a classification model for implementing condition-based maintenance (CBM) by monitoring the real-time status of a machine using acceleration sensor data collected from a vehicle. Methods: The classification model's performance was improved by applying Fourier transform to convert the acceleration sensor data from the time domain to the frequency domain. Additionally, the Generative Adversarial Network (GAN) algorithm was used to augment images and further enhance the classification model's performance. Results: Experimental results demonstrate that the GAN algorithm can effectively serve as an image augmentation technique to enhance the performance of the classification model. Consequently, the proposed approach yielded a significant improvement in the classification model's accuracy. Conclusion: While this study focused on the effectiveness of the GAN algorithm as an image augmentation method, further research is necessary to compare its performance with other image augmentation techniques. Additionally, it is essential to consider the potential for performance degradation due to class imbalance and conduct follow-up studies to address this issue.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.15-26
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• 2023

The purpose of this study is to determine the artificial intelligence-based degradation index from the image of the cross-section of the microstructure taken with a scanning electron microscope of the specimen obtained by the creep test of DA-5161 SX, a nickel-based superalloy used as a material for high-temperature parts. It proposes a new method of quantification and proposes a model that predicts degradation based on Bayesian inference without destroying components of high-temperature parts of operating equipment and a creep life prediction model that predicts Larson-Miller Parameter (LMP). It is proposed that the new degradation indexing method that infers a consistent representative value from a small amount of images based on the geometrical characteristics of the gamma prime phase, a nickel-base superalloy microstructure, and the prediction method of degradation index and LMP with information on the environmental conditions of the material without destroying high-temperature parts.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06b
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• pp.23-28
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• 1996

Model-based coding is one of several approaches to very low bit rate image coding and it can be used in many applications such as image creation and virtual reality. However, its analysis and synthesis processes remain difficult, especially in the sense that the resulting synthesized image reveals some degradation in detailed facial components such as furrows around eyes and mouth. To solve the problem, a large number of methods have been proposed and the texture update method is one of them. In this paper, we investigate texture synthesis for model-based coding. In the update process of the proposed texture synthesis algorithm, texture information is stored in a memory and the decoder reuses it. With this method, the transmission bit rate for texture data can be reduced compared with the conventional method updating texture periodically.

• Journal of Applied Reliability
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• v.7 no.3
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• pp.127-136
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• 2007

The accelerated life tests(ALTs) and degradation characteristics of image intensifier assembly(KIT-7) under low illuminance and high temperature were investigated. The accelerated life tests were carried out at $5{\times}10^5\;fc-40^{\circ}C,\;10{\times}10^5\;fc-40^{\circ}C,\;5{\times}10^5\;fc-50^{\circ}C,\;10{\times}10^5\;fc-50^{\circ}C$ and relationship related to illuminance and temperature was used as an accelerated life test model. An ALTA program[6] was used to calculate an acceleration factor and the test of life distribution fit, and estimate three parameters of an life test model. To sum up, MTTF 10,000 h at $5{\times}10^{-5}\;fc-40^{\circ}C$ of image intensifier assembly was certificated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2749-2763
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• 2021

The desirable result of infrared (IR) and visible (VIS) image fusion should have textural details from VIS images and salient targets from IR images. However, detail information in the dark regions of VIS image has low contrast and blurry edges, resulting in performance degradation in image fusion. To resolve the troubles of fuzzy details in dark regions of VIS image fusion, we have proposed a method of reflectance estimation for IR and VIS image fusion. In order to maintain and enhance details in these dark regions, dark region approximation (DRA) is proposed to optimize the Retinex model. With the improved Retinex model based on DRA, quasi-Newton method is adopted to estimate the reflectance of a VIS image. The final fusion outcome is obtained by fusing the DRA-based reflectance of VIS image with IR image. Our method could simultaneously retain the low visibility details in VIS images and the high contrast targets in IR images. Experiment statistic shows that compared to some advanced approaches, the proposed method has superiority on detail preservation and visual quality.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.411-414
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• 2010

As high quality image is required for digital cameras in recent use, the image stabilization technique has drawn much attention to prevent image degradation from shaky disturbance by users. In this paper, the optical image stabilization (OIS) system for DSLR (Digital Single Lens Reflex) camera is considered. First, the analytic model of an OIS system is presented to demonstrate the mechanism of image destabilization due to unknown disturbance that causes blurry images on CCD sensor. Then, to enhance the stabilization performance, a sliding mode control based on the min-max nonlinear control is introduced. Through the experiments and simulations, the effectiveness of the proposed method will be verified.

• International journal of advanced smart convergence
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• v.1 no.1
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• pp.6-13
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• 2012

An improved algorithm for image quality assessment is presented. First a simple model of human visual system, consisting of a nonlinear function and a 2-D filter, processes the input images. This filter has one user-defined parameter, whose value depends on the reference image. This way the algorithm can adapt to different scenarios. In the next step the average value of locally computed correlation coefficients between the two processed images is found. This criterion is closely related to the way in which human observer assesses image quality. Finally, image quality measure is computed as the average value of locally computed correlation coefficients, adjusted by the average correlation coefficient between the reference and error images. By this approach the proposed measure differentiates between the random and signal dependant distortions, which have different effects on human observer. Performance of the proposed quality measure is illustrated by examples involving images with different types of degradation.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.9
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• pp.66-75
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• 1999

Image segmentation is the process where an image is segmented into regions that are set of homogeneous pixels. The result has a ciritical effect on accuracy of image understanding. In this paper, an Markov random field (MRF) image segmentation is proposed using genetic algorithm(GA). We model an image using MRF which is resistant to noise and blurring. While MRF based methods are robust to degradation, these require accurate parameter estimation. So GA is used as a segmentation algorithm which is effective at dealing with combinatorial problems. The efficiency of the proposed method is shown by experimental results with real images and application to automatic vehicle extraction system.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.115-121
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• 2013

The first geostationary satellite in Korea, COMS (Communication, Ocean, and Meteorological Satellite), has been operating properly since its successful completion of the IOT (In Orbit Test). COMS MI (Meteorological Imager) acquires Earth observation images from visible and infrared channels. This paper describes a method to compute the degradation of the COMS visible detectors and the result of the degradation during the two years of the operation. The visible channel detectors' performance was determined based on the comparison between the instrument-based measurements and ROLO model-based values. The degradation rate of the visible channel detectors of COMS MI showed a normal condition.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.169-181
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• 1997

In this paper, we propose and discuss about image enhancement techniques for MPEG-4. which represents very low bit-rate, content-based. and object-based hierarchical audio-visual coding standard. The proposed enhancement technique removes undesired artifacts arising in the compression procedure and increase resolution in both spatial and temporal domains. In order to remove undesired artifacts. we divide the MPEG-4 video algorithm in two parts: MPEG-2 like part and the new part. For removing artifacts caused by the first part. we adopt the conventional blocking artifacts algorithm developed for MPEG-2. On the other hand for removing artifacts caused by the second part. we provide a new degradation model. and propose the corresponding image restoration method. For increasing resolution of the MPEG-4 images, we propose a general framework of multichannel image interpolation process. which includes both spatial and temporal interpolations. As the MPEG-4 standard is under development. various sophisticated techniques are considered. but research on image enhancement techniques is relatively underestimated. By this reason. additional image enhancement techniques will become very important issue in realization phase of MPEG-4.