• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.706-715
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• 2004

In this paper, to decide the watermark embedding positions and embed the watermark we use the subband tee structure which is presented in the wavelet domain and the edge information in the spatial domain. The significant frequency region is estimated by the subband searching from the higher frequency subband to the lower frequency subband. LH1 subband which has the higher frequency in tree structure of the wavelet domain is divided into 4${\times}$4 submatrices, and the threshold which is used in the watermark embedding is obtained by the blockmatrix which is consists by the average of 4${\times}$4 submatrices. Also the watermark embedding position, Keymap is generated by the blockmatrix for the energy distribution in the frequency domain and the edge information in the spatial domain. The watermark is embedded into the wavelet coefficients using the Keymap and the random sequence generated by LFSR(Linear feedback shift register). Finally after the inverse wavelet transform the watermark embedded image is obtained. the proposed watermarking algorithm showed PSNR over 2㏈ and had the higher results from 2％ to 8％ in the comparison with the previous research for the attack such as the JPEG compression and the general image processing just like blurring, sharpening and gaussian noise.

• The Journal of the Acoustical Society of Korea
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• v.19 no.1
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• pp.97-102
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• 2000

Subband coding is to divide the signal frequency band into a set of uncorrelated frequency bands by filtering and then to encode each of these subbands using a bit allocation rationale matched to the signal energy in that subband. The actual coding of the subband signal can be done using waveform encoding techniques such as PCM, DPCM and vector quantizer(VQ) in order to obtain higher data compression. Most researchers have focused on the error in the quantizer, but not on the overall reconstruction error and its dependence on the filter bank. This paper provides a thorough analysis of subband codecs and further development of optimum filter bank design using vector quantizer. We compute the mean squared reconstruction error(MSE) which depends on N the number of entries in each code book, k the length of each code word, and on the filter bank coefficients. We form this MSE measure in terms of the equivalent quantization model and find the optimum FIR filter coefficients for each channel in the M-band structure for a given bit rate, given filter length, and given input signal correlation model. Specific design examples are worked out for 4-tap filter in 2-band paraunitary filter bank structure. These optimum paraunitary filter coefficients are obtained by using Monte Carlo simulation. We expect that the results of this work could be contributed to study on the optimum design of subband codecs using vector quantizer.

• Speech Sciences
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• v.14 no.2
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• pp.127-135
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• 2007

Feature vectors of speech are generally extracted from whole frequency domain. The inherent character of a speaker is located in the low band or high band frequency. However, if the speech is corrupted by narrowband noise with concentrated energy, speaker verification performance is reduced as the individual characteristic is removed. In this paper, we propose a PCA Covariance Model based on the multiband to extract the robust feature vectors against the narrowband noise. First, we divide the overall frequency band into several subbands. Second, the correlation of feature vectors extracted independently from each subband is removed by PCA. The distance obtained from each subband has different distribution. To normalize against the different distribution, we moved the value into the normalized distribution through the mapping function. Finally, the represented value applying the weighting function is used for speaker verification. In the experiments, the proposed method shows better performance of the speaker verification and reduces the computation.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.9
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• pp.781-786
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• 2005

The binding energy in the n-type $GaAs/Al_xGa_{1-x}As$ quantum well is calculated. The shooting method, modified from the finite difference method, is used for the calculation of the subband energy level and its wave function. In order to account tot the change of the potential energy due to the charged particles, impurities and electrons, the self consistent method is employed. The wave function used for the calculation of the binding energy is assumed to be composed of the envelope function and hydrogenic 1s function. Then, the binding energies calculated by taking into account lot two different types of the hydrogenic 1s function are compared.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1409-1415
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• 2010

In this paper we proposed the watermarking technique using the markspace which is selected by tree-structure between the subbands in the wavelet domain and feature information in the spatial domain. The watermarking candidate region in the wavelet domain is obtained by the markspace selection algorithm divides the highest frequency subband to several segments and calculates theirs energy and the averages value of the total energy of the subband. Also the markspace of the spatial domain is obtained by the boundary information of a image. The final markspace is selected by the markspaces of the wavelet and spatial domain. The watermark is embedded into the selected markspace using the random addresses by LFSR. Finally the watermarking image is generated using the inverse wavelet transform. The proposed watermarking algorithm shows the robustness against the attacks such as JPEG, blurring, sharpening, and gaussian noise.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.236-237
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• 2019

In this paper, we propose a wavelet - based image noise reduction algorithm. We develop wavelet transform of existing Mallat Tree method. First, we propose a multiple filtering method. Maximizes the energy concentration characteristic of the wavelet transform considering the energy of each subband in the wavelet domain. We apply the proposed multiple filtering to the noise image. Finds energy subbands that can not be seen in normal images and removes them to remove noise.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.2
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• pp.14-26
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• 2002

A new model for degenerate semiconductor quantum well devices was developed. In this model, the multi-subband Boltzmann transport equation was formulated by applying the Pauli exclusion principle and coupled to the Schrodinger and Poisson equations. For the solution of the resulted nonlinear system, the finite difference method and the Newton-Raphson method was used and carrier energy distribution function was obtained for each subband. The model was applied to a Si MOSFET inversion layer. The results of the simulation showed the changes of the distribution function from Boltzmann like to Fermi-Dirac like depending on the electron density in the quantum well, which presents the appropriateness of this modeling, the effectiveness of the solution method, and the importance of the Pauli -exclusion principle according to the reduced size of semiconductor devices.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.796-804
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• 2002

This paper presents a new algorithm of fingerprint image analysis and processing using directional filter bank(DFB). The directional components of ridge is very important in pre-processing steps of fingerprint image processing such as image enhancement by directional filtering followed by estimationg the directional image of ridge patterns. The DFB analyzes input image into directional subband images and synthesizes them to the perfectly reconstructed image. In this paper, a new fingerprint processing algorithm using the DFB is proposed. The algorithm decomposes the fingerprint image into directional subband images and performs directional map generation, foreground segmentation, singular points extraction and image enhancement based on local directional energy estimate.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.3
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• pp.287-293
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• 1988

This paper calculates the band structure of the GaAs/(Al,Ga) As semiconductor superlttice with the interface3 grading, in consideration of different effective masses in each region. Including the effective masses, superlattice period, well and barrier widths, and the interface, the dispersion relation is derived, and the effects that the above parameters affect the subband (or miniband) structure of the superlattice and effective energy gap are investigated. It is particularly found that this case(ma<>mb<>mc) is significantly different from the same effective mass case(ma<>mb<>mc).

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.11 no.2
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• pp.49-57
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• 2007

In fingerprints, singular regions including core or delta points have different directional characteristics from non-singular regions. Generally, the ridges of singular regions change more abruptly than those of nonsingular areas, thus in order to effectively enhance fingerprint images regardless of region, local ridge curvature information needs to be used. In this paper, we present an improved Directional Filter Bank (DFB)-based fingerprint image enhancement method that effectively takes advantage of such ridge curvature information. The proposed method first decomposes a fingerprint image into 8 directional subbands using the DFB and then classifies the image into background, low curvature, and high curvature regions using the directional energy estimates calculated from the subbands. Thereafter, the weight values for directional subband processing are determined using classification information and directional energy estimates. Finally, the enhanced image is obtained by synthesizing the processed subbands. The experimental results show that the proposed approach is effective in enhancing both singular and non-singular regions.