• Journal of Advanced Marine Engineering and Technology
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• 제38권6호
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• pp.716-722
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• 2014

In order to design the speed controller of the DC motor system, firstly, parameters estimation of the system must be preceded. In this paper, we proposed the application of genetic algorithm(GA) optimization in estimating the parameters of DC motor. Estimated models are considered both first and second order models, and each estimated model is optimized by minimizing three different types of the evaluation function of GA. Also, GA is imported in comparison with estimation result of numerical analysis method because of its power in searching entire solution space with more probability of finding the global optimum. Data for parameter estimation is acquired from input and output signals of the actual experiment device and the butterworth filter also designs for removing noise in the signals. Finally comparison between real data of the actual device and estimated models is presented to indicate effectiveness and resolution of proposed identification method.

• The KIPS Transactions:PartB
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• 제19B권2호
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• pp.93-98
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• 2012

Recently, we can easily create high resolution images with digital cameras for high-performance and make use them at variety fields. Especially, the image stitching method which adjusts couple of images has been researched. Image stitching can be used for military purposes such as satellites and reconnaissance aircraft, and computer vision such as medical image and the map. In this paper, we have proposed fast image stitching based on improved SURF algorithm using meaningful features in the process of images matching after extracting features from scenery image. The features are extracted in each image to find out corresponding points. At this time, the meaningful features can be searched by removing the error, such as noise, in extracted features. And these features are used for corresponding points on image matching. The total processing time of image stitching is improved due to the reduced time in searching out corresponding points. In our results, the processing time of feature matching and image stitching is faster than previous algorithms, and also that method can make natural-looking stitched image.

• Journal of the Korean Society of Radiology
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• 제9권3호
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• pp.139-145
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• 2015

When examining a patient using SPECT, gamma rays emitted from the body decrease or scatter. And when they reach the detector they spread in accordance with physical characteristics and geometric shapes of the scanner, quantitative analysis was difficult. For exact quantitative analysis of gamma rays emitted from the body, so that they must be considered to correction about PVE(partial volume effect). In this paper, sinogram filter was implemented to solve comprehensive PVE of SPECT. According to the results in which implemented filter was applied, partial volume effect caused by SPECT was removed. To compare proposed method and conventional method, PSNR(Peak Signal to Noise Ratio) was executed. As a result, proposed method was indicated as 7dB, conventional method was indicated as 14db respectively. dB(decibel) level of the proposed methods is lower, since the MSE(mean square error) becomes greater because scattered ray was removed, PSNR value is low. Therefore, by applying the proposed method for removing the PVE of SPECT imaging method, the image quality is improved.

• Journal of the Institute of Convergence Signal Processing
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• 제1권1호
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• pp.23-31
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• 2000

Iterative curve evolution techniques are powerful methods for image segmentation. Classical methods proposed curve evolutions which guarantee close contours at convergence and, combined with the level set method, they easily handled curve topology changes. In this paper, we present a new geometric active contour model based on level set methods introduced by Osher & Sethian for detection of object boundaries or shape and we adopt anisotropic diffusion filtering method for removing noise from original image. Classical methods allow only one-way curve evolutions : shrinking or expanding of the curve. Thus, the initial curve must encircle all the objects to be segmented or several curves must be used, each one totally inside one object. But our method allows a two-way curve evolution : parts of the curve evolve in the outward direction while others evolve in the inward direction. It offers much more freedom in the initial curve position than with a classical geodesic search method. Our algorithm performs accurate and precise segmentations from noisy images with complex objects(jncluding sharp angles, deep concavities or holes), Besides it easily handled curve topology changes. In order to minimize the processing time, we use the narrow band method which allows us to perform calculations in the neighborhood of the contour and not in the whole image.

• Korean Journal of Remote Sensing
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• 제36권4호
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• pp.535-544
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• 2020

In synthetic aperture radar (SAR) based ship detection application, false alarms frequently occur due to various noises caused by the radar imaging process. Among them, radio frequency interference (RFI) and azimuth smearing produce substantial false alarms; the latter also yields longer length estimation of ships than the true length. These two noises are prominent at cross-polarization and relatively weak at co-polarization. However, in general, the cross-polarization data are suitable for ship detection, because the radar backscatter from background sea surface is much less in comparison with the co-polarization backscatter, i.e., higher ship-sea image contrast. In order to improve the ship detection accuracy further, the RFI and azimuth smearing need to be mitigated. In the present letter, Sentinel-1 VV- and VH-polarization intensity data are used to show a novel technique of removing these noises. In this method, median image intensities of noises and background sea surface are calculated to yield arithmetic tendency. A band-math formula is then designed to replace the intensities of noise pixels in VH-polarization with adjusted VV-polarization intensity pixels that are less affected by the noises. To verify the proposed method, the adaptive threshold method (ATM) with a sliding window was used for ship detection, and the results showed that the 74.39% of RFI false alarms are removed and 92.27% false alarms of azimuth smearing are removed.

• Journal of the Korean Geophysical Society
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• 제2권2호
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• pp.143-152
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• 1999

We have studied a denoising technique involving wavelet transform for improving the quality of geophysical data during the preprocessing stage. To assess the effectiveness of this technique, we have made synthetic data contaminated by random noises and compared the results of denoising with those obtained by conventional low-pass filtering. The low-pass filtering of the sinusoidal signal having a sharp discontinuity between the first and last sample values shows apparent errors related to Gibbs' phenomena. For the case of bump signal, the low-pass filtering induces maximum errors on peak values by removing some high-frequency components of signal itself. The wavelet transform technique, however, denoises these signals with much less adverse effects owing to its pertinent properties on locality of wavelet and easy discrimination of noise and signal in the wavelet domain. The field data of gravity tide are denoised by using soft threshold, which shrinked all the wavelet coefficients toward the origin, and the G-factor is determined by comparing the denoised data and theoretical data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제20권5호
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• pp.39-43
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• 2020

In this paper, we propose the multi-channel interference cancellation algorithm for visible light communication (VLC) in smart building. The VLC system is communication technology using visible rays that come out in Light Emitting Diode (LED) device. It has energy curtailment effect and possible to use in ubiquitous network service applications. When a large number of users communicate indoors, the performance can be reduced due to channel interference. To remove interference, at the first, the minimum mean square error (MMSE) scheme as interference cancellation methods used, and then the successive interference cancellation (SIC) is applied to obtain additional diversity gain and improve interference cancellation performance. Indoor VLC channel model is employed. The performance is evaluated in terms of bit error rate (BER). From the simulation results, it is confirmed that the proposed scheme has better BER performance compared to the previous systems. As a result, the proposed interference cancellation improves the signal quality of VLC systems by effectively removing the channel noise. The results of the paper can be applied to VLC for smart building and general communication systems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• 제46권6호
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• pp.132-145
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• 2009

We present the framework for JND based Illumination and Color Restoration Using Edge-preserving filter for restoring distorted images taken under the arbitrary lighting conditions. The proposed method is effective for appropriate illumination compensation, vivid color restoration, artifacts suppression, automatic parameter estimation, and low computation cost for HW implementation. We show the efficiency of the mean shift filter and sigma filter for illumination compensation with small spread parameter while considering the processing time and removing the artifacts such as HALO and noise amplification. The suggested CRF (color restoration filter) can restore the natural color and correct color distortion artifact more perceptually compared with current solutions. For the automatic processing, the image statistics analysis finds suitable parameter using JND and all constants are pre-defined. We also introduce the ROI-based parameter estimation dealing with small shadow area against spacious well-exposed background in an image for the touch-screen camera. The object evaluation is performed by CMC, CIEde2000, PSNR, SSIM, and 3D CIELAB gamut with state-of-the-art research and existing commercial solutions.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• 제24권8호
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• pp.119-125
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• 2010

This paper proposes a new solution about physical problem of autonomous mobile robots system using ultrasonic sensors. An mobile robot uses several sensors for recognition of its circumstance. However, such sensor data are not accurate all the time. A means of removing the noise that sensor data contains constantly, It is possible for simulation to estimate its circumstance based on ultrasonic sensor data by learning algorithm SVR(Support Vector Regression). To use SVR, it is being selected parameter and kernel which are the component of SVR. Selecting the component of SVR, the most accurate parameter data was selected through the tests because it is not existed determined data. In addition, choosing the kernel uses RBF(Radial Basis Function) kernel which is the most generalized. This paper proposes SVR based algorithm to compensate for the above demerits of ultrasonic sensor through the experimentation under three different environments.

• Journal of the Korean Institute of Intelligent Systems
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• 제22권3호
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• pp.341-346
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• 2012

In rehabilitation where ultrasonographic diagnosis is not popular, it could be subjective by medical expert's experience. Thus, it is necessary to develop an objective automative procedure in ultrasonic image analysis. A disadvantage of existing automative analytic procedure in musculoskeletal system is to designate an incorrect muscle area when the figure of fascia is vague. In this study, we propose a new procedure to extract more accurate muscle area in abdomen ultrasonic image for that purpose. After removing unnecessary noise from input image, we apply End-in Search algorithm to enhance the contrast between fascia and muscle area. Then after extracting initial muscle area by Up-Down search, we trace the fascia area with a mask based on morphological and directional information. By this tracing of mask movements, we can emphasize the fascia area to extract more accurate muscle area in result. This new procedure is proven to be more effective than existing methods in experiment using convex ultrasound images that are used in real world rehabilitation diagnosis.