• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1749-1752
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• 2005

For online high accurate reconstruction of an object from an visual information, a linear reconstruction method for multiple images is popular. Basically this method needs many cameras or many different screen shots from different view points. This method, however, has the benefit of less calculation and is adequate for a real time application by comparing other popular method. In this paper, online reconstruction system using more than three cameras is treated. An evaluation method of cameras' position, and of the number is derived for the linear reconstruction method. To decrease errors that are caused from skew of lens, positional error between corresponding points is taken into consideration on the evaluation. The proposed evaluation method enables estimation of the adequate number of cameras and then of feasible view locations. Additionally, repeating search of epipolar lines enables estimation of the hidden point. Comparing with result of an average error analysis, it was confirmed that the proposed methods works effectively.

• The Journal of the Acoustical Society of Korea
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• v.20 no.6
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• pp.9-16
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• 2001

This paper deals with the inverse reconstruction of sectional area in nonuniform ducts by using the acoustical measurement. There have been many theoretical and experimental studies on the duct area reconstruction. In this research, the method using the impulse response function and area reconstruction algorithm was employed because of its mathematical and experimental simplicity. Based on the study results on the drawback of conventional impulse excitation method, a new measurement method is proposed, that uses the random noise source and the discrete inverse Fourier transform. It is found that the reconstruction errors of the present method is smaller than the conventional method. A random error analysis is performed in order to investigate the causes of reconstruction error and to clarify the applicable data range for area reconstruction.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.6
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• pp.615-622
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• 2015

Recently Digital-TachoGraph(DTG) was mounted mandatorily in commercial vehicles(Taxi, Bus, etc.). DTG records accurate and detailed information of the running state of vehicles related to traffic accident, such as Time, Distance, Velocity, RPM, Brake ON/OFF, GPS, Azimuth, Acceleration. Thus those standardized data can play an important role in traffic accident investigation and reconstruction. To develope the accurate and objective method using the DTG data for the reconstruction of traffic accident, we had conducted several tests such as driving test, high speed circuit test, braking test, slalom test at Korea Automobile Testing & Research Institute(KATRI), and collision test at Korea Automobile insurance repair Research and Training center(KART) with the vehicle equipped with several DTG. Development of the program which enables the reading and analysis of the DTG data was followed. In the experiments, we have found velocity error, RPM error, brake signal error and azimuth error in several products, and also non-continuous event data. The cause of these errors was deduced to be related to the correction factor, the durability of electronic parts and the algorithm.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.104-110
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• 2014

This paper considers two reconstruction schemes of structured-sparse signals, turbo inference and Markov chain Monte Carlo (MCMC) inference, in compressed sensing(CS) technique that is recently getting an important issue for an efficient video wireless transmission system using multi-copter as an unmanned aerial vehicle. Proposed reconstruction algorithms are setting importance on reduction of image data sizes, fast reconstruction speed and errorless reconstruction. As a result of experimentation with twenty kinds of images, we can find turbo reconstruction algorithm based on loopy belief propagation(BP) has more excellent performances than MCMC algorithm based on Gibbs sampling as aspects of average reconstruction computation time, normalized mean squared error(NMSE) values.

• ETRI Journal
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• v.35 no.2
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• pp.200-206
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• 2013

Most of the literature on compressed sensing has not paid enough attention to scenarios in which the number of acquired measurements is insufficient to satisfy minimal exact reconstruction requirements. In practice, encountering such scenarios is highly likely, either intentionally or unintentionally, that is, due to high sensing cost or to the lack of knowledge of signal properties. We analyze signal reconstruction performance in this setting. The main result is an expression of the reconstruction error as a function of the number of acquired measurements.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.138-145
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• 1997

This paper proposes an adaptive algorithm for the quantization step size control of MPEG-2, using the information obtained from the previously encoded picture. Before quantizing the DCT coefficients, the properties of reconstruction error of each macro block (MB) is predicted from the previous frame. For the prediction of the error of current MB, a block with the size of MB in the previous frame are chosen by use of the motion vector. Since the original and reconstructed images of the previous frame are available in the encoder, we can calculate the reconstruction error of this block. This error is considered as the expected error of the current MB if it is quantized with the same step size and bit rate. Comparing the error of the MB with the average of overall MBs, if it is larger than the average, small step size is given for this MB, and vice versa. As a result, the error distribution of the MB is more concentrated to the average, giving low variance and improved image quality. Especially for the low bit application, the proposed algorithm gives much smaller error variance and higher PSNR compared to TM5 (test model 5).

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.85-88
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• 2000

Signal splitting and perfect reconstruction in subband coding is based on the assumption that quantization errors are negligible. But if subband signal is quantized, 4 types of errors occurs thus it is not impossible to do perfect reconstruction. These errors are QMF design error, aliasing error, signal error and random error. By using the QMF for subband splitting, the QMF error does not present. and by using the Lloyd-Max quantizer for the quantization and by using an appropriate synthesis filter, all signal dependent errors can be cancelled and the remaining error is random error which is uncorrelated with the original image〔1〕. In this thesis, Lenna and Camera-Man image are devided into 10 subbands by using the D4 and D20 wavelet And the subband signals are quantized by using the Lloyd-Max quantizer and the quantization errors are compared. and evaluated.

• Journal of the Korean Institute of Gas
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• v.25 no.5
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• pp.63-69
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• 2021

In this study, we established an algorithm to determine whether the work in the gas facility is a normal work or an abnormal work using the threshold of the reconstruction error of the autoencoder. This algorithm do deep learning the autoencoder only with time-series data of a normal work, and derives the optimized threshold of the reconstruction error of the normal work. We applied this algorithm to the time series data of the new work to get the reconstruction error, and then compare it with the reconstruction error threshold of the normal work to determine whether the work is normal work or abnormal work. In order to train and validate this algorithm, we defined the work in a virtual gas facility, and constructed the training data set consisting only of normal work data and the validation data set including both normal work and abnormal work data.

• Journal of the Optical Society of Korea
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• v.20 no.4
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• pp.515-523
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• 2016

Spectral reflectance is sparse in space, and while the traditional spectral-reconstruction algorithm does not make full use of this characteristic sparseness, the compressive sensing algorithm can make full use of it. In this paper, on the basis of analyzing compressive sensing based on the orthogonal matching pursuit algorithm, a new algorithm based on the Dice matching criterion is proposed. The Dice similarity coefficient is introduced, to calculate the correlation coefficient of the atoms and the residual error, and is used to select the atoms from a library. The accuracy of Spectral reconstruction based on the pseudo-inverse method, Wiener estimation method, OMP algorithm, and DOMP algorithm is compared by simulation on the MATLAB platform and experimental testing. The result is that spectral-reconstruction accuracy based on the DOMP algorithm is higher than for the other three methods. The root-mean-square error and color difference decreases with an increasing number of principal components. The reconstruction error decreases as the number of iterations increases. Spectral reconstruction based on the DOMP algorithm can improve the accuracy of color-information replication effectively, and high-accuracy color-information reproduction can be realized.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.77-82
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• 1996

This paper is concerned with how to utilize kinematic redundancy to reconstruct the inverse kinematic solution which is not attainable due to hardware limitations. By analyzing the error due to hardware limitations, we are to show that the recoverability of limitation reduces to the solvability of a reconstruction equation under the feasibility condition. It will be next shown that the reconstruction equation is solvable if the configuration is not a joint-limit singularity. The reconstruction method will be proposed based on the geometrical analysis of recoverability of hardware limitations. The method has the feature that no task motion error is induced by the hardware limitations while minimizing a possible null motion error, under the recoverability assumed.