• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.12 s.117
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• pp.1185-1191
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• 2006

The radiated noise of the excavator is composed of the various noise sources such as the diesel engine, cooling fan and hydraulic system, so the noise reduction for each noise source is required. In this study, the source contribution analysis for these principal noise sources is performed by using the noise source removal method. And to reduce the noise due to each one, the various experiments and analyses are studied. On the basis of these results, the proper noise reduction countermeasures are derived to develop the excavator satisfied the $2^{nd}$ noise regulation of EU.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2928-2947
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• 2015

Adaptive Gaussian filter (AGF) is a recently developed switching filter to remove salt and pepper noise. AGF first directly identifies pixels of gray levels 0 and 255 as noise pixels, and then only restored noise pixels using a Gaussian filter with adaptive variance based on the estimated noise density. AGF usually achieves better denoising effect in comparison with other filters. However, AGF still fails to obtain good denoising effect on images with noise-free pixels of gray levels 0 and 255, due to its severe false alarm in its noise detection stage. To alleviate this issue, a modified version of AGF is proposed in this paper. Specifically, the proposed filter first performs noise detection via an image block based noise density estimation and sequential noise density guided rectification on the noise detection result of AGF. Then, a modified Gaussian filter with adaptive variance and window size is used to restore the detected noise pixels. The proposed filter has been extensively evaluated on two representative grayscale images and the Berkeley image dataset BSDS300 with 300 images. Experimental results showed that the proposed filter achieved better denoising effect over the state-of-the-art filters, especially on images with noise-free pixels of gray levels 0 and 255.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.409-412
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• 2005

Just as the vibration modes of a beam are dependent on its end constraints or boundary conditions. Vibration modes of a tire are dependent on its patch and spindle constraints. This dependence is key to understanding the dynamic properties of a tire and is apparent in various analytical and experimental investigations in the literature. One of the main task in a modal analysis is the measurement of the Frequency Response Function (FRFs). Because all the subsequent analysis is based on these FRFs, their quality is critically important in obtaining accurate modal parameter estimates. In rotating systems, FRFs are frequently contaminated by harmonic peaks related to such factors as imbalance, misalignment. This harmonic peaks appear in the FRFs as sharp spikes, which can be erroneously treated in modal curve-fitting procedures as structural modes. The harmonic peaks removal method is demonstrated by application to modal analysis on rotating tires. The results show substantial improvement in FRF quality.

• The Journal of the Korea Contents Association
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• v.14 no.12
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• pp.555-564
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• 2014

The boundary noise in image syntheses using DIBR consists of noisy pixels that are separated from foreground objects into background region. It is generated mainly by edge misalignment between the reference image and depth map or blurred edge in the reference image. Since hole areas are generally filled with neighboring pixels, boundary noise adjacent to the hole is the main cause of quality degradation in synthesized images. To solve this problem, a new boundary noise removal algorithm using a preprocessing of the depth map is proposed in this paper. The most common way to eliminate boundary noise caused by boundary misalignment is to modify depth map so that the boundary of the depth map can be matched to that of the reference image. Most conventional methods, however, show poor performances of boundary detection especially in blurred edge, because they are based on a simple boundary search algorithm which exploits signal gradient. In the proposed method, a two-step hierarchical approach for boundary detection is adopted which enables effective boundary detection between the transition and background regions. Experimental results show that the proposed method outperforms conventional ones subjectively and objectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.675-681
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• 2022

Recently, with the development of IoT technology and AI, unmanned and automated in various fields, interest in video processing, which is the basis for automation such as object recognition and object classification, is increasing. Various studies have been conducted on noise removal in the video processing process, which has a significant impact on image quality and system accuracy and reliability, but there is a problem that it is difficult to restore images for areas with high impulse noise density. In this paper proposes a filter algorithm based on partial mask and Lagrange interpolation to restore the damaged area of impulse noise in the image. In the proposed algorithm, the filtering process was switched by comparing the filtering mask with the noise estimate and the purge weight was calculated based on the low frequency component and the high frequency component of the image to restore the image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1846-1852
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• 2021

In modern society, various digital devices are being distributed in a wide range of fields due to the fourth industrial revolution and the development of IoT technology. However, noise is generated in the process of acquiring or transmitting an image, and not only damages the information, but also affects the system, causing errors and incorrect operation. AWGN is a representative noise among image noise. As a method for removing noise, prior research has been conducted, and among them, AF, A-TMF, and MF are the representative methods. Existing filters have a disadvantage that smoothing occurs in areas with high frequency components because it is difficult to consider the characteristics of images. Therefore, the proposed algorithm calculates the standard deviation distribution to effectively eliminate noise even in the high frequency domain, and then calculates the final output by applying the probability density function weight of the Laplace distribution using the curve fitting method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.165-171
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• 2000

The study about a drainpipe of water closet was performed as reduction plan on drainage noise for water closet, which of noise in plumbing systems was being indicated the major point at issue in apartment houses. A drainpipe of water closet is divided into a sleeve, a joint elbow and a traversing pipe, through the result of experiment, for an effective noise reduction in a drainpipe a threefold joint elbow is proposed among parts. And through the experiment of performance with glasswool, the removal of glasswool should be in the economical efficiency aspect.

• International Journal of Contents
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• v.5 no.4
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• pp.1-6
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• 2009

In this paper, we propose a mesh smoothing method for mesh models with noise. The proposed method enables not only the removal of noise from the vertexes but the preservation and smoothing of shape recognized as edges and comers. The magnitude ratio of 2D area and 3D volume in mesh data is adopted for the smoothing of noise. Comparing with previous smoothing methods, this method does not need many iteration of the smoothing process and could preserve the shape of original model. Experimental results demonstrate improved performance of the proposed approach in 3D mesh smoothing.

• Journal of Industrial Technology
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• v.26 no.A
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• pp.89-93
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• 2006

Pulse oximetry, which monitors non-invasively the oxygen saturation in blood, is influenced by patient's respiration, movement or a factor of an environment. Specially, it's difficult to measure a PPG (Photoplethsmography) signal from the moving patient because of the motion artifact. Accordingly, it is required to extract the pure PPG signal from the PPG signal to measure oxygen saturation. In this paper, we propose an adaptive noise canceller to improve the performance of motion artifact removal. Then we design a hardware system for real time monitoring of the oxygen saturation. The proposed algorithm estimates the slope of transition rate between two different wavelength signals.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.157-160
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• 2010

Terrestrial LiDAR data contains outliers which do not need in processing purpose. That is inefficient in the aspect of productivity. These noise requires manual process to be removed, which causes inefficiency in aspect of productivity. The purpose of this research is to demonstrate a possibility of automatic outlier removal of LiDAR data using 3D Tensor Voting method. For this, we presented in this article about the procedure to perform the application of Tensor Voting algorithm to the real data from terrestrial LiDAR.