• Title/Summary/Keyword: Fourier 변환

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Effects of fractional fourier transform of facial images in face recognition using eigenfeatures (고유특징을 이용한 얼굴인식에 있어서 얼굴영상에 대한 분수차 Fourier 변환의 효과)

  • 심영미;장주석
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.35C no.8
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    • pp.60-67
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    • 1998
  • We studied the effects of fractional fourier transform in face recognition, in which only the amplitude spectra of transformed facial images were used.We used two recently developed face recognition methods, the most effective feature (MEF) method (i.e., eigenface method) and most discriminating feature (MDF) method, and the effects of th etransform for th etwo methods were consistent. We confirmed that the recognition rate by the use of MDF method is better than that consistent. We confirmed that the recognition rate by the use of MDF method is better than that by MEF regardless of the order to transform, these methods provided slightly better results when the order was 1 than for any other order values. Only when the order was close to 1, the recognition rates were robust to the shift of the input images, and the trend that the recognition rates decreased as the input size varied was independent of the order. From these results, we fond that it is most advantageous to use the amplitude spectra of the conventional fourier transform whose order is 1.

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Feature Extraction of Fault Current using Fourier Transform in the Multi-Shot Reclosing Scheme (푸리에 변환을 이용한 다중 재폐로방식에서의 사고전류 특징 추출)

  • O, Jeong-Hwan;Yun, Sang-Yun;Kim, Jae-Cheol
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.49 no.2
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    • pp.50-55
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    • 2000
  • This paper presents the feature extraction of fault currents related to the multi-shot reclosing scheme in the power distribution system. In order to get the fault current waveform, we have measured the fault currents by the fault recorders which have been installed at the secondary side of 154/22.9[kV] substation transformer. These waveforms are classified into temporary and permanent fault. For the classified waveforms, Fourier transform is used to extract the feature of the fault current waveforms. After the waveforms are analyzed by using Fourier transform, the magnitude spectrum and the relative variation of THD (Total Harmonic Distortion) are calculated. And then the relative variation of THD is great in the temporary faults, and is small in the permanent faults.

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A Study on Signal Analyser Design using Fast Walsh Transform (고속월쉬변환을 이용한 신호분석기 설계에 관한 연구)

  • Han, Sang-Wook;Shin, Seung-Kwon;Park, Jun-Hun;Oh, Min-Whan;Han, Sang-In;Ahn, Du-Su
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.2614-2616
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    • 2000
  • This paper presents the Walsh-Fourier conversion algorithm and Signal Analysis Technique. The Fourier coefficients are determined as the combinations of the Walsh coefficients in terms of the new Walsh-Fourier conversion algorithm. This paper checks the analysis of the Walsh-Fourier spectra and the approximate synthesis of the waveform via one example.

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Shift-invariant face recognition based on the karhunen-loeve approximationof amplitude spectra of fourier-transformed faces (Fourier 변환된 얼굴의 진폭스펙트럼의 karhunen-loeve 근사 방법에 기초한 변위불변적 얼굴인식)

  • 심영미;장주석;김종규
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.35C no.3
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    • pp.97-107
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    • 1998
  • In face recognition based on the Karhunen-Loeve approximation, amplitudespectra of Fourier transformed facial images were used. We found taht the use of amplitude spetra gives not only the shift-invariance property but also some improvment of recognition rate. This is because the distance between the varing faces of a person compared with that between the different persons perfomed computer experiments on face recognitio with varing facial images obtained from total 55 male and 25 females. We confirmed that the use of amplitude spectra of Fourier-trnsformed facial imagesgives better recognition rate for avariety of varying facial images including shifted ones than the use of direct facial images does.

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Texture Feature Extractor Based on 2D Local Fourier Transform (2D 지역푸리에변환 기반 텍스쳐 특징 서술자에 관한 연구)

  • Saipullah, Khairul Muzzammil;Peng, Shao-Hu;Kim, Hyun-Soo;Kim, Deok-Hwan
    • Proceedings of the Korea Information Processing Society Conference
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    • 2009.04a
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    • pp.106-109
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    • 2009
  • Recently, image matching becomes important in Computer Aided Diagnosis (CAD) due to the huge amount of medical images. Specially, texture feature is useful in medical image matching. However, texture features such as co-occurrence matrices can't describe well the spatial distribution of gray levels of the neighborhood pixels. In this paper we propose a frequency domain-based texture feature extractor that describes the local spatial distribution for medical image retrieval. This method is based on 2D Local Discrete Fourier transform of local images. The features are extracted from local Fourier histograms that generated by four Fourier images. Experimental results using 40 classes Brodatz textures and 1 class of Emphysema CT images show that the average accuracy of retrieval is about 93%.

De-Noising of Electroretinogram Signal Using Wavelet Transforms (웨이브렛 변환을 이용한 망막전도 신호의 잡음제거)

  • Seo, Jung-Ick;Park, Eun-Kyoo
    • Journal of Korean Ophthalmic Optics Society
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    • v.17 no.2
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    • pp.203-207
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    • 2012
  • Purpose: Electroretinogram(ERG) signal noise as well as conducting other bio-signal measurement were generated. It was intened to enhance the accuracy of retinal-related diagnosis with removing signal noise. Methods: Sampling signal was made with generating 60 Hz noise and white noise. The noise were removed using wavelet transforms and bandpass filter. De-noising frequency was compared with Fourier transform spectrum. Removed noises were compared numerically using SNR(signal to noise ratio). Results: The result compared Fourier transform spectrum was showed that 60 Hz noise removed completely and most of white noise was removed by wavelet transforms. 60 Hz and the white noise remained using bandpass filters. The result compared SNR showed that wavelet transforms was 22.8638 and bandpass filter was 4.0961. Conclusions: Wavelet transform showed less signal distortion in removing noise. ERG signal is expected to improve the accuracy of retinal-related diagnosis.

Soil Particle Shape Analysis Using Fourier Descriptor Analysis (퓨리에 기술자 분석을 이용한 단일 흙 입자의 형상 분석)

  • Koo, Bonwhee;Kim, Taesik
    • Journal of the Korean GEO-environmental Society
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    • v.17 no.3
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    • pp.21-26
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    • 2016
  • Soil particle shape analysis was conducted with sands from Jumujun, Korea and Ras Al Khair, Saudi Arabia. Two hundred times enlarged digital images of the particles of those two sands were obtained with an optical microscope. The resolution of the digital images was $640{\times}320$. By conducting digital image processing, the coordinates of the soil particle boundary were extracted. After mapping those coordinates to the complex space, Fourier transformation was performed and the coefficients of each trigonometry term were computed. The coefficients reflect the shape characteristics of the sand grains and are invariant to translation. To evaluate the shape itself excluding the size of the soil particle, the coefficient was normalized by the equivalent radius of soil particle; this is called Fourier descriptor. After analyzing the Fourier descriptors, it was found that the major characteristics of Jumunjin and Ras Al Khair sands were elongation and asymmetry. Furthermore, it was found that the particle shapes reflect the self-similar, fractal nature of the textural features. The effects of resolution on soil particle shape analysis was also studied. Regarding this, it was found that the significant Fourier descriptors were not significantly affected by the image resolution investigated in this study, but the descriptors associated with textural features were affected.

Forecasts of electricity consumption in an industry building (광, 공업용 건물의 전기 사용량에 대한 시계열 분석)

  • Kim, Minah;Kim, Jaehee
    • The Korean Journal of Applied Statistics
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    • v.31 no.2
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    • pp.189-204
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    • 2018
  • This study is on forecasting the electricity consumption of an industrial manufacturing building called GGM from January 2014 to April 2017. We fitted models using SARIMA, SARIMA + GARCH, Holt-Winters method and ARIMA with Fourier transformation. We also forecasted electricity consumption for one month ahead and compared the predicted root mean square error as well as the predicted error rate of each model. The electricity consumption of GGM fluctuates weekly and annually; therefore, SARIMA + GARCH model considering both volatility and seasonality, shows the best fit and prediction.

A Fast Parameter Estimation of Time Series Data Using Discrete Fourier Transform (이산푸리에변환과 시계열데이터의 고속 파라미터 추정)

  • Shim, Kwan-Shik;Nam, Hae-Kon
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.55 no.7
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    • pp.265-272
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    • 2006
  • This paper describes a method of parameter estimation of time series data using discrete Fourier transform(DFT). DFT have been mainly used to precisely and rapidly obtain the frequency of a signal. In a dynamic system, a real part of a mode used to learn damping characteristics is a more important factor than the frequency of the mode. The parameter estimation method of this paper can directly estimate modes and parameters, indicating the characteristics of a dynamic system, on the basis of the Fourier transform of the time series data. Real part of a mode estimates by subtracting a frequency of the Fourier spectrum corresponding to 0.707 of a magnitude of the peak spectrum from a peak frequency, or subtracting a frequency of the power spectrum corresponding to 0.5 of the peak power spectrum from a peak frequency, or comparing the Fourier(power) spectrum ratio. Also, the residue and phase of time signal calculate by simple equation with the real part of the mode and the power spectrum that have been calculated. Accordingly, the proposed algorithm is advantageous in that it can estimate parameters of the system through a single DFT without repeatedly calculating a DFT, thus shortening the time required to estimate the parameters.

Strain Analysis using Fourier Transform Grid Method and Its Image Processing (퓨리에 변환 격자법과 화상 처리를 이용한 스트레인 해석)

  • Yang, In-Hong
    • Journal of the Korean Society for Precision Engineering
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    • v.9 no.3
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    • pp.165-171
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    • 1992
  • 진동하는 구조물을 설계할 때에는 그 구조물 중의 Strain이나 응력이 최대가 되는 장소나 시각을 알 필요가 있다. 지금까지의 Strain 해석에는 Strain gauge 등과 같은 접촉법이 많이 이용되고 있다. 더우기, 접촉법으로 대변형 진동을 하는 물체의 Strain을 해석하는 것은 곤란하다. 최근에는 비접촉법으로 Strain 분포를 해석하기 위해 화상처리를 이용한 계측이 행하여지고 있다. 이들의 Strain 분포를 측정하는 광학적인 방법으로는 격자법, Moire법, 홀로 그랩픽 간섭법 등이 있다. 특히 대변형이나 대Strain을 해석하는 데에는 격자법이 많이 이용되고 있는데, 종래의 격자법은 Data를 처리하는 데에 많은 시간과 노력이 소요되고 작업도 매우 복잡하며, Data의 수도 제한이 되어서 구조물의 분포의 해석 정도에 큰 영향을 미치게 된다. 본 논문 에서는 스테레오법을 이용해서 2차원 격자를 붙인 시료표면의 각 점의 3차원 좌표를 계측하고, 또 Fourier 변환 격자법을 적용하여 촬영된 2차원 격자의 화상에서 위상치를 구한다. 그리고 물체의 변형 전후의 대응 관계의 화상에서 3차원 형상과 Strain 분포를 해석하는 방법을 제안한다. 이 방법을 이용하면 진동하는 구조 물의 3차원 변위분포, Strain 분포를 정도 좋게 해석할 수가 있다.

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