• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1996년도 추계학술대회
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• pp.225-228
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• 1996

ECG data are used for the diagnostic purposes with many clinical situations, especially heart disease. In this paper, an efficient ECG data compression technique by wavelet transform and high-speed vector quantization on PMS-B algorithm is proposed. In general, ECG data compression techniques are divided into two categories: direct and transform methods. The direct data compression techniques are AZTEC, TP, CORTES, FAN and SAPA algorithms, besides the transform methods include K-L, Fourier, Walsh, and wavelet transforms. In this paper, we applied wavelet analysis to the ECG data. In particular, vector quantization on PMS-B algorithm to the wavelet coefficients in the higher frequency regions, but scalar quantized in the lower frequency regions by PCM. Finally, the quantized indices were compressed by LZW lossless entropy encoder. As the result of simulation, it turns out to get sufficient compression ratio while keeping clinically acceptable PRD.

• 대한의용생체공학회:의공학회지
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• 제38권4호
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• pp.211-217
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• 2017

During the emergency situation such as cardiac arrest, cardiopulmonary resuscitation(CPR) is the most important treatment to maintain patient's blood circulation. Since the quality of CPR can not be easily measured or evaluated by the eye, an assistive device with an accelerometer can help to assess the pressure depth of CPR. In this study, we propose a single frequency analysis method to reduce the error of the accelerometer by extracting only one frequency component from the Fourier transform process. To verify the effectiveness of the single frequency analysis, acceleration data at CPR conditions were measured at a sampling rate of 50 / sec using a wristband equipped with an acceleration sensor. Then, We compared the existing distance estimation method and the single frequency analysis method using the measured data. The amplitude value proportional to the compression depth was obtained by applying the single frequency analysis method.

• 한국통신학회논문지
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• 제24권12B호
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• pp.2407-2414
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• 1999

본 논문에서는 WDCT(Warped Discrete Cosine Transform)의 개념에 대해서 소개하고 이의 응용분야로서 WDCT를 이용한 영상 압축 알고리듬을 제시한다. WDCT는 기존의 일반적인 DCT와 주파수 특성이 하나의 파라미터로 조절되는 IIR(infinte impulse response) 전대역 통과 필터(all-pass filter)를 직렬로 연결한 변환이다. 제시된 영상 압축 알고리듬에서는 필터의파라미터가 미리 정의된 범위 내에서 조절되도록 한다. 각 영상의 블록에 대해서 주어진 범위 내에서 가장 좋은 파라미터가 선정되면 이를 이용한 WDCT의 결과와 이 파라미터를 디코더로 전송한다. 본 논문에서는 IIR 전대역 통과 필터링 과정을 하나의 행렬로 대체하거나 DCT를 필터뱅크로 보아 IIR 필터와 DCT의 결합을 일반적인 DCT와 마찬가지로 하나의 행렬로 표현하였다. 따라서 주어진 파라미터에 따라 각각 다른 새로운 WDCT 행렬을 정의할 수 있으므로 WDCT의 결과는 행렬과 벡터의 곱으로 얻어진다. WDCT를 이용한 영상 압축의 결과는 높은 비트율과 고주파 성분이 많은 영상에 대하여 DCT의 성능보다 우수함을 알 수 있었다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1998년도 봄 학술발표회 논문집
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• pp.335-340
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• 1998

The apparently different physical problems of lateral vibration and elastic stability of a linear member are limiting cases of a single phenomenon, the more general expression being the mode of vibration with end thrust. For a single-span beam-column, it is generally known that the square of the frequency of lateral vibration is approximately linearly related to compressive axial force. In this paper the relationship between the frequency and axial force of multi-span compression members is investigated by means of the finite element method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1662-1665
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• 2004

A real-time joint transform correlator by using JPEG-compressed reference images is proposed as practical solution to storage problem and improvement of processing time of automatic target recognition system [1]. Effects of compression on recognition performance of join transform correlator are quantitatively investigated under situations where the target is suffered from noise and has contrast difference with respect to the reference. Two images with different spatial-frequency contents and contrast were used as the test scenes. The simulation results show that, the recognition performance of joint transform correlator by using the compressed reference images with high spatial-frequency components is more sensitive to noise and contrast difference than the low spatial-frequency image.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 정기총회 및 추계학술대회 논문집 학회본부
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• pp.338-341
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• 1993

A EEG(ElectroEncephaloGram) compression scheme based on subband coding techniques is presented in this paper. Considering the frequency characteristics of EEG, the raw signal was decomposed into different frequency bands. After decomposition, optimal bit allocation was done by adapting to the standard deviation in each frequency bands, and decomposed signals were quantized using pdf(probability density function)-optimized nonuniform quantizer. Based on the above mentioned coding scheme, coding results of various multichannel EEG signal were shown with compression ratio and SNR(signal-to-noise ratio).

• 한국통신학회논문지
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• 제22권3호
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• pp.493-505
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• 1997

In this paper, a wavelet image compression method using human visually estimated quantizer is proposed. The quantizer has three components. These are constructed by using effects of frequency band, background luminance, and spatial masking. The first quantization factor is a fixed constant value for each band. The second factor is calculated by averaging four wavelet coefficients in the lowest frequency band. The third factor is determined by the difference between wavelet coefficients in the lowest frequency band. Arithmetic coding is used for encoding quantized wavelet coefficients. Coefficients in the lowest band are transmitted without loss. Therefore the compressed image is decompressed by using three quantization factors which can be calculated in the receiver. Compared with previous image compression methods which adopted human visual system, the proposed method shows improved results with less computational cost.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.1875-1878
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• 2003

This paper Proposes a wavelet-based video compression method to improve compressed images using modification of wavelet coefficients. In conventional wavelet-based compression methods, bigger coefficients are transmitted early according to the significance of the coefficients. In this reason, when some coefficients which have more significance but are not bigger are not transmitted, image degradation occurs. The Proposed method considered two human visual characteristics. First, human eyes are more sensitive to the change of middle frequency which represents abrupt change of brightness than that of high frequency which expresses fine region. Second, human eyes are more dull to color component than luminance respectively. By adjusting the coefficients of wavelet transformed signals and allocating more bits for compression to the luminance signal, higher compression could be achieved.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.333-334
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• 2006

In this study, information compression based on the wavelet technique is described. The principle of signal or image compression is performed by optimization of quantization, that is the bit allocation taking advantage of their energy concentration in low frequency components. The wavelet transform is one of frequency decomposition, such as the discrete cosine transform or sub-band filtering, and it is also implemented as a filter bank. Wavelet transform with use of spatially localized basis function can reduce several drawbacks in conventional methods. The benifit of wavelet based compression method is described as comparing the transform method to another ones.

• 전기학회논문지
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• 제58권11호
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• pp.2292-2298
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• 2009

In this paper, the lossy image compression algorithm using the quad tree and the bandlets is proposed. The proposed algorithm transforms input images by the discrete wavelet transform (DWT) and represents the geometrical structures of high frequency bands using the bandlets with a 8 block- size. In addition, the proposed algorithm searches the position information of the significant coefficients by using the quad tree algorithm and computes the magnitude and the sign information of the significant coefficients by using the Embedded Image Coding using Zerotrees of Wavelet Coefficients (EZW) algorithm. The compression result by using the quad tree algorithm improves the PSNR performance of high frequency images up to 1 dB, compared to that of JPEG-2000 algorithm and that of S+P algorithm. The PSNR performance by using DWT and bandlets improves up to 7.5dB, compared to that by using only DWT.