• Journal of Digital Contents Society
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• v.17 no.6
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• pp.593-601
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• 2016

This paper is related to the Region-based Spectral Correlation Estimation(RSCE) coding method that makes it possible to achieve the high-compression ratio by estimating color component images from luminance image. The proposed method is composed of three steps. First, Y/C bit-plane summation image is defined using normalized chrominance summation image and luminance image, and then the Y/C bit-plane summation image is segmented for extracting the shape information of the regions. Secondly, the scale factor and the offset factor minimizing the approximation square errors between luminance image and R, B images by the each region are calculated. Finally, the scale factor and the offset factor for the each region are encoded into bit stream. Referring to the results of computer simulation, the proposed method provides more than two or three times higher compression ratio than JPEG/Baseline or JPEG2000/EBCOT algorithm in terms of bpp needed for encoding two color component images with the same PSNR.

• The Journal of the Acoustical Society of Korea
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• v.24 no.3
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• pp.150-159
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• 2005

This paper addresses a voice personality transformation algorithm which makes one person's voices sound as if another person's voices. In the proposed method, one person's voices are represented by LPC cepstrum, pitch period and speaking rate, the appropriate transformation rules for each Parameter are constructed. The Gaussian Mixture Model (GMM) is used to model one speaker's LPC cepstrums and conditional probability is used to model the relationship between two speaker's LPC cepstrums. To obtain the parameters representing each probabilistic model. a Maximum Likelihood (ML) estimation method is employed. The transformed LPC cepstrums are obtained by using a Minimum Mean Square Error (MMSE) criterion. Pitch period and speaking rate are used as the parameters for prosody transformation, which is implemented by using the ratio of the average values. The proposed method reveals the superior performance to the previous VQ-based method in subjective measures including average cepstrum distance reduction ratio and likelihood increasing ratio. In subjective test. we obtained almost the same correct identification ratio as the previous method and we also confirmed that high qualify transformed speech is obtained, which is due to the smoothly evolving spectral contours over time.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.49-58
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• 2006

In this paper, a curve-fitting channel estimation method is proposed for orthogonal frequency division multiplexing (OFDM) system in a time-varying frequency-selective fading channel. The method can greatly improve channel state information (CSI) estimation accuracy by performing smoothing and interpolation through consecutive curve-fitting processes in both time domain and frequency domain. It first evaluates least-squares (LS) estimates using pilot symbols and then the estimates are approximated to a polynomial with proper degree in the LS error sense, starting from one preferred domain in which pilots we densely distributed. Smoothing, interpolation, and prediction are performed subsequently to obtain CSI estimates for data transmission. The channel estimation processes are completed by smoothing and interpolating CSI estimates in the other domain once again using the channel estimates obtained in one domain. The performance of proposed method is influenced heavily on the time variation and frequency selectivity of channel and pilot arrangement. Hence, a proper degree of polynomial and an optimum approximation interval according to various system and channel conditions are required for curve-fitting. From extensive simulation results in various channel environments, we see that the proposed method performs better than the conventional methods including the optimal Wiener filtering method, in terms of the mean square error (MSE) and bit error rate (BER).

• The Journal of the Acoustical Society of Korea
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• v.32 no.1
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• pp.22-31
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• 2013

In this paper, we propose a method that estimates the channel response from underwater communication signals with MMSE (Minimun Mean Squared Error) and detects dominant components automatically based on power of response components using CFAR (Constant False Alarm Rate). Statistical characteristics are analyzed with variation of magnitude and phase and time coherence via experimental data obtained by drifting transmitter and receiver. We show that bit error rate has small difference, 1.2 times, compared with the case using every channel information estimated within data period when estimation and equalization is performed with extracted characteristic obtained by the proposed method.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.98-98
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• 2017

대부분의 가정과 요식업체, 식품가공업계에서 이용하고 있는 식용유지는 저장 및 가공과정 중에 산패가 빈번하게 일어나게 된다. 기존에는 유지 산패를 측정하기 위해 산가, 과산화물가 등을 측정하는 이화학적인 적정방법을 이용하였는데 실험자의 숙련도에 따라 결과의 오차가 발생할 수 있고, 반복실험으로 인한 시간과 비용이 많이 소모되는 등 여러 제약사항을 포함하고 있어 식용유지의 산패를 실시간 비파괴적으로 분석할 수 있는 기술의 개발에 많은 관심이 모아지고 있다. 따라서, 본 연구에서는 식용유지의 저장조건에 따른 산패정도를 비파괴적으로 평가하기 위한 근적외선 분광분석과 인공신경망 분석기술을 개발하여 그 실효성을 평가하였다. 식물성 식용유지인 들기름을 특정 온도에서 일정한 시간동안 저장하면서 이화학적 적정방법을 통해 산가와 과산화물가를 측정하였으며 동일한 시료의 근적외선 투과스펙트럼을 획득하였다. 수집된 정보를 이용하여 유지 산패 예측 모델을 개발하기 위해 다변량 분석기법 (주성분 회귀분석, 최소자승 회귀분석과 인공신경망 분석)을 적용하였다. 분석 결과, 인공신경망 분석모델이 산가 ($R^2_{tra}:0.9037$, $R^2_{val}:0.8175$, $R^2_{test}:0.8555$)와 과산화물가 ($R^2_{tra}:0.9210$, $R^2_{val}:0.9341$, $R^2_{test}:0.8286$)의 예측 성능이 가장 우수한 것으로 확인되었다. 본 연구의 결과들은 농산물과 식품의 성분 측정뿐만 아니라 다른 산업분야에서도 유용하게 활용될 수 있을 것으로 기대되어진다.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.115-124
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• 2010

VDF(volume-delay function) is one of the most important factor to improve the reliability of traffic demand estimation because it is for estimation of link travel time based on the traffic volume variation. Because VDF of link except for freeway is applied as the parameter of BPR(bureau of public road) of U.S., it causes to deteriorate the accuracy of traffic demand estimation. The purpose of this paper is to establish new parameter of VDF based on the real-surveyed traffic data in order to improve the problem of the existing VDF. We suggest the reclassification of road hierarchy, the approach of traffic survey, the estimating method of VDF parameter, and the improvements of new VDF application. The new VDF allows us to estimate more realistic traffic situation in parts of demand, travel time and path between origin-destination.

• The Korean Journal of Nuclear Medicine
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• v.32 no.5
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• pp.414-424
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• 1998

Purpose: Cross-modality coregistration of positron emission tomography (PET) and magnetic resonance imaging (MR) could enhance the clinical information. In this study we propose a refined technique to improve the robustness of registration, and to implement more realistic visualization of the coregistered images. Materials and Methods: Using the sinogram of PET emission scan, we extracted the robust head boundary and used boundary-enhanced PET to coregister PET with MR. The pixels having 10% of maximum pixel value were considered as the boundary of sinogram. Boundary pixel values were exchanged with maximum value of sinogram. One hundred eighty boundary points were extracted at intervals of about 2 degree using simple threshold method from each slice of MR images. Best affined transformation between the two point sets was performed using least square fitting which should minimize the sum of Euclidean distance between the point sets. We reduced calculation time using pre-defined distance map. Finally we developed an automatic coregistration program using this boundary detection and surface matching technique. We designed a new weighted normalization technique to display the coregistered PET and MR images simultaneously. Results: Using our newly developed method, robust extraction of head boundary was possible and spatial registration was successfully performed. Mean displacement error was less than 2.0 mm. In visualization of coregistered images using weighted normalization method, structures shown in MR image could be realistically represented. Conclusion: Our refined technique could practically enhance the performance of automated three dimensional coregistration.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.353-356
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• 2005

In this paper, the proposed $gamma({\gamma})$ line system is developed for reducing the error between non-linear gamma curve produced by a formula and result produced by hardware implementation. The proposed algorithm and system is based on the specific gamma value 2.2, namely the formula is represented by {0,1}$^{2.2}$ and the bit width of input and out data is 10bit. In order to reduce the error, the system is using least squares polynomial of the numerical method which is calculating the best fitting polynomial through a set of points. The proposed gamma line is consisting of nine kinds of quadratic equations, each with their own overlap sections to get more precise. Based on the algorithm verified by $MATLAB^{TM}$ 7.0, the proposed system is implemented by using Verilog-HDL. The proposed system has 2 clock latency; 1 result per clock. The error range (LSB) is -4 and +3. Its standard deviation is 1.287956238. The total gate count of system is 2,083 gates and the maximum timing is 15.56[ns].

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2011.10a
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• pp.255-269
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• 2011

The purpose of study has to analyze with non destructive method for researching the tool that could be measured with the status of record written on Hanji speedily. Because the original record should be destructed for analyzing with previous method in the case of the paper record, it was to develop the tool based on non destructive method for overcoming such limit. The study was used with FT NIR (Fourier transform NIR) for analyzing the Hanji for being written and preserved. The FT NIR spectrometer that of NIR spectrometer has the better performance of precision and accuracy than dispersive NIR spectrometer was used. Also the wavelength of FT-NIR was measured with 12,500 to 4,000 $cm^{-1}$, and the integrating sphere as diffuse reflectance type was used for analyzing Hanji. The moisture and acidity (pH) of chemical factors as quality evaluated factor of Hanji was studied for the correlation of NIR spectrum. And then The NIR spectrum was pretreated for showing the coefficients of optimum correlation. MSC and First derivative of Savitzky - Golay was used as pretreated method, and the coefficients of optimum correlation were shown by PLSR(Partial least square regression). And the coefficients of optimum correlation were calculated by PLSR(Partial least square regression). The correlation coefficients of acidity had 0.92 on NIR spectra without pretreatment. Also the SEP of acidity was 0.24. And then The NIR spectra with pretreatment would have more good correlation coefficients ($R^2=0.98$) and more good SEP(=019) on acidity. Therefore the data of correlation coefficients ($R^2$) and SEP with pretreatment was shown to be superior. And NIR spectra data of first derivative had best linearity on the correlation coefficients ($R^2=0.99$) and also SEP(=0.45) was superior. Therefore the correlation coefficients and SEP of first derivative had better than those of NIR spectra of no pretreatment. As such result, it was possible to evaluate the record status of Hanji speedily with integrated sphere and NIR analyzer as non destructive method.

• The Journal of the Acoustical Society of Korea
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• v.7 no.4
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• pp.54-76
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• 1988

In Part Ⅰ of the paper, we have developed various block least mean-square (BLMS) adaptive digital filters (ADF's) based on a unified matrix treatment. In Part Ⅱ we analyze the convergence behaviors of the self-orthogonalizing frequency-domain BLMS (FBLMS) ADF and the unconstrained FBLMS (UFBLMS) ADF both for the overlap-save and overlap-add sectioning methods. We first show that, unlike the FBLMS ADF with a constant convergence factor, the convergence behavior of the self-orthogonalizing FBLMS ADF is governed by the same autocorrelation matrix as that of the UFBLMS ADF. We then show that the optimum solution of the UFBLMS ADF is the same as that of the constrained FBLMS ADF when the filter length is sufficiently long. The mean of the weight vector of the UFBLMS ADF is also shown to converge to the optimum Wiener weight vector under a proper condition. However, the steady-state mean-squared error(MSE) of the UFBLMS ADF turns out to be slightly worse than that of the constrained algorithm if the same convergence constant is used in both cases. On the other hand, when the filter length is not sufficiently long, while the constrained FBLMS ADF yields poor performance, the performance of the UFBLMS ADF can be improved to some extent by utilizing its extended filter-length capability. As for the self-orthogonalizing FBLMS ADF, we study how we can approximate the autocorrelation matrix by a diagonal matrix in the frequency domain. We also analyze the steady-state MSE's of the self-orthogonalizing FBLMS ADF's with and without the constant. Finally, we present various simulation results to verify our analytical results.