• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.224-229
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• 2007

This paper presents a camera calibration method using several images for three dimensional measurement applications such as stereo systems, mobile robots, and visual inspection systems in factories. Conventional calibration methods that use single image suffer from errors related to reference point extraction in image, lens distortion, and numerical analysis of nonlinear optimization. The camera parameter values obtained from images of same camera is not same even though we use same calibration method. The camera parameters that are obtained from several images of different view for a calibration target is usaully not same with large error values and we can not assume a special probabilistic distribution when we estimate the parameter values. In this paper, the median value of camera parameters from several images is used to improve estimation of the camera values in an iterative step with nonlinear optimization. The proposed method is proved by experiments using real images.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.62-70
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• 2016

Increased bus traffic leads inefficiency at near-side bus stops in median exclusive bus lane because buses are waiting for a signal does not have a vehicle arrived. This study suggests a method for estimating a proper spacing between bus stops and signalized intersection to prevent the inefficiency. We modified the Poisson model for a proper spacing by using both dwell time and waiting time of signal instead of using dwell time only. The waiting time of signal changes by spacing and it was measured using micro simulation program. The iterative algorithm using the change of waiting time of signal was also suggested. By applying the proposed method, measure waiting time by simulation and iterative algorithm, the spacing of near-side bus stops, proper spacing is suggested according to flow rate level.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.361-366
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• 2015

The objective of this paper was to establish the attributes that determines neighbourhood satisfaction in South Africa lowincome housing subsidy scheme ultilising the Delphi approach. This is because the perception and housing satisfaction of lowincome housing beneficiaries toward their housing condition can be studied by examining their satisfaction toward s the neighbourhood factors. The Delphi method was used where the views of housing experts were solicited on 26 potential attributes as identified from li terature. Consensus was achieved after three iterative rounds. The expert"s scored each attributes on a 10-point ordinal scale of impact significance, where 1-2=No impact and 9-10= very high impact. The scales adapted for consensus were: strong consensus, median 9-10, inter quartile deviation (IQD) ≤1; good consensus, median 7 ≤ 6.99and IQD≥2.1≤3. The key findings indicate that there was a good to strong consensus of 19 attributes which were key attributes that the experts perceived as determinants of neighbourhood satisfaction; while 6 other attributes had weak consensus, as they were considered to have a le sser impact in determining residents" neighbourhood satisfaction. However, attributes with weak consensus were the attributes that are highly regarded as core neighbourhood factors in other housing settings. The study contributes to the body of knowledge on th e subject where no consensus has been reached pertaining to indicators for measuring neighbourhood satisfaction in subsidised low-income housing in South Africa.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.355-363
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• 2011

Recently, as one of several methods to improve the performance of DVC(Distributed Video Coding) system, many research works are focusing on the iterative refinement of side information. Most of the conventional techniques are mainly based on the relationship between the reconstruction level and side information, or the vector median filtering of motion vectors, but, their performance improvements are restricted. In order to overcome the performance limit of the conventional schemes, in this paper, a side information generation scheme is designed by measuring the block-cost estimation. Then, by adaptively selecting the compensation mode using the received bit-plane information, we propose a block-adaptive iterative refinement which is efficient for non-symmetric moving objects. Computer simulations show that, by using the proposed refinement method, the performance can be improved up to 0.2 dB in rate-distortion.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.193-196
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• 1995

An algorithm using topological mapping has been developed for a real-time detection of the QRS complexes of ECG signals. As a measurement of QRS complex energy, we used topological mapping from one dimensional sampled ECG signals to two dimensional vectors. These vectors are reconstructed with the sampled ECG signals and the delayed ones. In this method, the detection rates of CRS complex vary with the parameters such as R-R interval average and peak detection threshold coefficient. We use mean, median, and iterative method to determint R-R interval average and peak estimation. We experiment on various value of search back coefficient and peak detection threshold coefficient to find optimal rule.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.78.1-78.1
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• 2019

Using a method to correct redshift space distortion (RSD) for individual galaxies, we mapped the real space distributions of galaxies in the Sloan Digital Sky Survey (SDSS) Data Release 7(DR7). We use an ensemble of mock catalogs to demonstrate the reliability of this extension, showing that it allows for an accurate recovery of the real-space correlation functions and galaxy biases. We also demonstrate that, using an iterative method applied to intermediate scale clustering data, we can obtain an unbiased estimate of the growth rate of structure $f\sigma_8$, which is related to the clustering amplitude of matter, to an accuracy of $\sim 10\%$. Applying this method to the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7), we construct a real-space galaxy catalog spanning the redshift range $0.01 \leq z \leq 0.2$, which contains 584,473 galaxies in the North Galactic Cap (NGC). Using this data we, infer $0.376 \pm 0.038$ at a median redshift z=0.1, which is consistent with the WMAP9 cosmology at $1\sigma$ level. By combining this measurement with the real-space clustering of galaxies and with galaxy-galaxy weak lensing measurements for the same sets of galaxies, we are able to break the degeneracy between $f$, $\sigma_8$ and $b$. From the SDSS DR7 data alone, we obtain the following cosmological constraints at redshift $z=0.1$ for galaxies.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.175-182
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• 2017

Noises are usually generated by various external causes and low quality devices in image data acquisition and recording as well as by channel interference in image transmission. Since these noise signals result in the loss of information, subsequent image processing is subject to the corruption of the original image. In general, image processing is performed in the mixed noise environment where common types of noise, known to be Gaussian and impulse, are present. This study proposes an iterative weighted mean filter for reducing mixed type of noise. Impulse noise pixels are first turned off in the input image, then $3{\times}3$ sliding window regions are processed by replacing center pixel with the result of weighted mean mask operation. This filtering processes are iterated until all the impulse noise pixels are replaced. Applied to images corrupted by Gaussian noise with ${\sigma}=10$ and different levels of impulse noise, the proposed filtering method improved the PSNR by up to 12.98 dB, 1.97 dB, 1.97 dB respectively, compared to SAWF, AWMF, MMF when impulse noise desities are less than 60%.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1
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• pp.31-39
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• 1995

In this paper, we have constructed phoneme discriminant filters [PDF] according to the linear discriminant function. These discriminant filters do not follow the heuristic rules by the experts but the mathematical methods in iterative learning. Proposed system. is based on the piecewise linear classifier and error correction learning method. The segmentation of speech and the classification of phoneme are carried out simutaneously by the PDF. Because each of them operates independently, some speech intervals may have multiple outputs. Therefore, we introduce the unified coefficients by the output unification process. But sometimes the output has a region which shows no response, or insensitive. So we propose time windows and median filters to remove such problems. We have trained this system with the 549 monosyllables uttered 3 times by 3 male speakers. After we detect the endpoint of speech signal using threshold value and zero crossing rate, the vowels and consonants are separated by the PDF, and then selected phoneme passes through the following PDF. Finally this system unifies the outputs for competitive region or insensitive area using time window and median filter.