• Title/Summary/Keyword: gabor wavelet transform

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Automatic TFT-LCD Mura Defect Detection using Gabor Wavelet Transform and DCT (가버 웨이블렛 변환 및 DCT를 이용한 자동 TFT-LCD 패널 얼룩 검출)

  • Cho, Sang-Hyun;Kang, Hang-Bong
    • Journal of Broadcast Engineering
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    • v.18 no.4
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    • pp.525-534
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    • 2013
  • Recently, mura defect inspection techniques are receiving attention in LCD production procedure since demands of TFT-LCD are growing. In this paper, we propose an automatic mura defect inspection method using gabor wavelet transform and DCT. First, we generate a reference panel image using DCT based method. For original panel image and generated reference panel image, we apply a gabor wavelet transform to eliminate texture information in images. Then, we extract mura defect regions from the difference image between gabor wavelet transform image of original panel and generated reference panel image. Finally, all mura defect regions are quantified to detect accurate mura defects. Experimental results show that our method is more accurate and efficient than previous methods.

The Selection of the Optimal Gator Wavelet Shape Factor Using the Shannon Entropy Concept (Shannon 엔트로피 개념을 이용한 가보 웨이블렛 최적 형상의 선정)

  • Hong, Jin-Chul;Kim, Yoon-Young
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2002.11b
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    • pp.176-181
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    • 2002
  • The continuous Gabor wavelet transform (GWT) has been utilized as a useful time-frequency analysis tool to identify the rapidly-varying characteristics of some wave signals. In the application of GWT, it is important to select the Gabor wavelet with the optimal shape factor by which the time-frequency distribution of a signal can be accurately estimated. To find the signal-dependent optimal Gabor wavelet shape factor, the notion of the Shannon entropy which mesures the extent of signal energy concentration in the time-frequency plane is employed. To verify the validity of the present entropy-based scheme, we have applied it to the time-frequency analysis of a set of elastic bending wave signals generated by an impact in a solid cylinder.

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The Selection of the Optimal Gabor Wavelet Shape Factor Using the Shannon Entropy Concept (Shannon 엔트로피 개념을 이용한 가보 웨이블렛 최적 형상의 선정)

  • Hong, Jin-Chul;Kim, Yoon-Young
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2002.11a
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    • pp.324.1-324
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    • 2002
  • The continuous Gabor wavelet transform (GWT) has been utilized as a useful time-frequency analysis tool to identify the rapidly-varying characteristics of some wave signals. In the application of GWT, it is important to select the Gabor wavelet with the optimal shape factor by which the time-frequency distribution of a signal can be accurately estimated. To find the signal-dependent optimal Gator wavelet shape factor, the notion of the Shannon entropy which measures the extent of signal energy concentration in the time-frequency plane is employed. (omitted)

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The Improvement of Motion Compensation for a Moving Target Using the Gabor Wavelet Transform (Gabor Wavelet Transform을 이용한 움직이는 표적에 대한 움직임 보상 개선)

  • Shin, Seung-Yong;Myung, Noh-Hoon
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.17 no.10 s.113
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    • pp.913-919
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    • 2006
  • This paper presents a technique for motion compensation of ISAR(Inverse SAR) images for a moving target. If a simple fourier transform is employed to obtain ISAR image for a moving target, the image is usually blurred. These images blurring problem can be solved with the time-frequency transform. In this paper, motion compensation algorithms of ISAR image such as STFT(Short Time Fourier Transform), GWT(Gabor Wavelet Transform) are described. In order to show the performances of each algorithm, we use scattering wave of the ideal point scatterers and simulated MIG-25 to obtain motion compensated ISAR image, and display the resolution of STFT and GWT ISAR image.

Texture Feature-Based Language Identification Using Gabor Feature and Wavelet-Domain BDIP and BVLC Features (Gabor 특징과 웨이브렛 영역의 BDIP와 BVLC 특징을 이용한 질감 특징 기반 언어 인식)

  • Jang, Ick-Hoon;Lee, Woo-Shin;Kim, Nam-Chul
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.4
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    • pp.76-85
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    • 2011
  • In this paper, we propose a texture feature-based language identification using Gabor feature and wavelet-domain BDIP (block difference of inverse probabilities) and BVLC (block variance of local correlation coefficients) features. In the proposed method, Gabor and wavelet transforms are first applied to a test image. The wavelet subbands are next denoised by Donoho's soft-thresholding. The magnitude operator is then applied to the Gabor image and the BDIP and BVLC operators to the wavelet subbands. Moments for Gabor magnitude image and each subband of BDIP and BVLC are computed and fused into a feature vector. In classification, the WPCA (whitened principal component analysis) classifier, which is usually adopted in the face identification, searches the training feature vector most similar to the test feature vector. Experimental results show that the proposed method yields excellent language identification with rather low feature dimension for a document image DB.

A Study on the Wavelet Transform of Acoustic Emission Signals Generated from Fusion-Welded Butt Joints in Steel during Tensile Test and its Applications (맞대기 용접 이음재 인장시험에서 발생한 음향방출 신호의 웨이블릿 변환과 응용)

  • Rhee, Zhang-Kyu
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.16 no.1
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    • pp.26-32
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    • 2007
  • This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform(WFT or STFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform(WT) is used to decompose the acoustic emission(AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

A Study on the Wavelet Transform of Acoustic Emission Signals Generated from Fusion-Welded Butt Joints in Steel during Tensile Test and its Applications (맞대기 용접 이음재 인장시험에서 발생한 음향방출 신호의 웨이블릿 변환과 응용)

  • Rhee Zhang-Kyu;Yoon Joung-Hwi;Woo Chang-Ki;Park Sung-Oan;Kim Bong-Gag;Jo Dae-Hee
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2005.05a
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    • pp.342-348
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    • 2005
  • This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform (WFT or SIFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform (WT) is used to decompose the acoustic emission (AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

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Soft Thresholding Method Using Gabor Cosine and Sine Transform for Image Denoising (영상 잡음제거를 위한 게이버 코사인과 사인 변환의 소프트 문턱 방법)

  • Lee, Juck-Sik
    • Journal of the Institute of Convergence Signal Processing
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    • v.11 no.1
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    • pp.1-8
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    • 2010
  • Noise removal methods for noisy images have been studied a lot in the domain of spatial and transform filtering. Low pass filtering was initially applied in the spatial domain. Recently, discrete wavelet transform has widely used for image denoising as well as image compression due to an excellent energy compaction and a property of multiresolution. In this paper, Gabor cosine and sine transform which is considered as human visual filter is applied to image denoising areas using soft thresholding technique. GCST is compared with excellent wavelet transform which uses existing soft thresholding methods from PSNR point of view. Resultant images removed noises are also visually compared. Experimental results with adding four different standard deviation levels of Gaussian distributed noises to real images show that the proposed transform has better PSNR performance of a maximum of 1.18 dB and visible perception than wavelet transform.

Robust iris recognition for local noise based on wavelet transforms (국부잡음에 강인한 웨이블릿 기반의 홍채 인식 기법)

  • Park Jonggeun;Lee Chulhee
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.2 s.302
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    • pp.121-130
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    • 2005
  • In this paper, we propose a feature extraction method for iris recognition using wavelet transforms. The wavelet transform is fast and has a good localization characteristic. In particular, the low frequency band can be used as an effective feature vector. In iris recognition, the noise caused by eyelid the eyebrow, glint, etc may be included in iris. The iris pattern is distorted by noises by itself, and a feature extraction algorithm based on filter such as Wavelets, Gabor transform spreads noises into whole iris region. Namely, such noises degrade the performance of iris recognition systems a major problem. This kind of noise has adverse effect on performance. In order to solve these problems, we propose to divide the iris image into a number of sub-region and apply the wavelet transform to each sub-region. Experimental results show that the performance of proposed method is comparable to existing methods using Gabor transform and region division noticeably improves recognition performance. However, it is noted that the processing time of the wavelet transform is much faster than that of the existing methods.

Identification of Mass-Lines and Rigid Body Properties using Wavelet Transform (웨이블렛 변환을 이용한 질량선 및 강체특성의 규명)

  • 안세진;정의봉;황대선
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2002.05a
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    • pp.115-120
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    • 2002
  • The rigid body properties of a structure may be estimated easily if the mass-line of the structure could be taken exactly. However, the exact mass-line may be hard to be obtained exactly in experiments. The mass line value can be read from the mass line in frequency response function. However, the mass lines in the frequency response function sometimes show the fluctuation with frequency, and it cannot be read correctly. In this paper, the wavelet transform is applied to obtain the good mass line value. The mass line calculated by using wavelet transform has unique value and showed in the range of fluctuated values of frequency response function. The rigid body properties obtained by wavelet transform also showed better results than those by fourier transform.

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