Gabor Wavelet

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Donald J. Kouri - One of the best experts on this subject based on the ideXlab platform.

  • Shannon–Gabor Wavelet distributed approximating functional
    Chemical Physics Letters, 1998
    Co-Authors: David K. Hoffman, G.w. Wei, D. S. Zhang, Donald J. Kouri
    Abstract:

    Abstract The Shannon sampling theorem is critically reviewed from a physical point of view. An approximate sampling formula is proposed, combining Shannon sampling with a Gabor-distributed approximating functional (DAF) window function, which results in new Shannon–Gabor Wavelet DAFs (SGWDs). They are extremely smooth, decay rapidly, have simultaneous time-frequency localization, and are also generalized delta sequences (reducing to the Dirac delta function under the limit of a zero window width). Shannon's sampling theorem is recovered exactly when the window is infinitely wide.Finally, SGWDs are well-behaved L 2 ( R ) kernels, and thus can be used for solving differential equations.

  • shannon Gabor Wavelet distributed approximating functional
    Chemical Physics Letters, 1998
    Co-Authors: David K. Hoffman, G.w. Wei, D. S. Zhang, Donald J. Kouri
    Abstract:

    Abstract The Shannon sampling theorem is critically reviewed from a physical point of view. An approximate sampling formula is proposed, combining Shannon sampling with a Gabor-distributed approximating functional (DAF) window function, which results in new Shannon–Gabor Wavelet DAFs (SGWDs). They are extremely smooth, decay rapidly, have simultaneous time-frequency localization, and are also generalized delta sequences (reducing to the Dirac delta function under the limit of a zero window width). Shannon's sampling theorem is recovered exactly when the window is infinitely wide.Finally, SGWDs are well-behaved L 2 ( R ) kernels, and thus can be used for solving differential equations.

A. Mostafa - One of the best experts on this subject based on the ideXlab platform.

  • A method for texture classification of ultrasonic liver images based on Gabor Wavelet
    Proceedings 7th International Conference on Signal Processing 2004. Proceedings. ICSP '04. 2004., 2004
    Co-Authors: Alireza Ahmadian, A. Mostafa, M.d. Abolhassani, N.r. Alam
    Abstract:

    In this paper we proposed a new method for texture classification of ultrasonic liver images based on Gabor Wavelet. It is well known that Gabor Wavelets attain maximum joint space-frequency resolution which is highly significant in the process of texture extraction in which the conflicting objectives of accuracy in texture representation and texture spatial localization are both important. This fact has been explored in our results as it shows that the classification rate obtained by Gabor Wavelet is higher that those obtained using dyadic Wavelets. The feature vector consists of 10 elements at each scale from Gabor Wavelets which is relatively small compared to other methods. This has a significant impact on the speed of retrieval process. The proposed algorithm applied to discriminate ultrasonic liver images into three disease states that are normal liver, liver hepatitis and cirrhosis. In our experiment 45 liver sample images from each three disease states which already proven by needle biopsy were used. We achieved the sensitivity 85% in the distinction between normal and hepatitis liver images and 86% in the distinction between normal and cirrhosis liver images. Based on our experiments, the Gabor Wavelet is more appropriate than dyadic Wavelets for texture classification as it leads to higher classification accuracy.

  • An efficient texture classification algorithm using Gabor Wavelet
    Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439), 1
    Co-Authors: Alireza Ahmadian, A. Mostafa
    Abstract:

    In this paper we have investigated the application of nonseparable Gabor Wavelet transform for texture classification. We have compared the effect of applying the dyadic Wavelet transform as a traditional method with Gabor Wavelet for texture extraction. It is well known that Gabor Wavelets attain maximum joint space-frequency resolution which is highly significant in the process of texture extraction in which the conflicting objectives of accuracy in texture representation and texture spatial localization are both important. This fact has been explored in our results as they show that the classification rate obtained for Gabor Wavelet is higher that those obtained using dyadic Wavelets. Based on our experiments, the Gabor Wavelet is more appropriate than dyadic Wavelets for texture classification as it leads to a better discrimination of textures.

Alireza Ahmadyfard - One of the best experts on this subject based on the ideXlab platform.

  • retinal blood vessel segmentation using Gabor Wavelet and line operator
    International Journal of Machine Learning and Computing, 2012
    Co-Authors: Reza Kharghanian, Alireza Ahmadyfard
    Abstract:

    In this paper, we propose a method for segmenting blood vessels from retinal images. We extract two sets of features for image classification: features based on Gabor Wavelet and line operator. At each pixel of retinal image we construct a feature vector consisting of the pixel intensity, four features from Gabor Wavelet transform in different scales and two features from orthogonal line operators. We compare the result of classification using two classifiers: Bayesian and SVM. First we estimate class-conditional probability density functions for vessel and non-vessel using Gaussian mixture model. Then using a Bayesian classifier we implement a fast classification. The result of experiments show the combination of Gabor features and line features provides a good performance for vessel segmentation. We tested the proposed algorithm on DRIVE database which is publicly available. As the second classifier we employ Support Vector Machine. The results shows SVM classifier in some cases performs better than Bayesian classifier.

  • defect detection in textiles using morphological analysis of optimal Gabor Wavelet filter response
    International Conference on Computer and Automation Engineering, 2009
    Co-Authors: Hamid Alimohamadi, Alireza Ahmadyfard, Esmaeil Shojaee
    Abstract:

    This paper addresses new defect detection method in textile based on Morphological Analysis and Gabor Wavelet filters responses. Our method consist of there part. First a bank of Gabor Wavelet filters is applied on the textile image for extracting feature matrix. It is based on the energy response from the convolution of Gabor Wavelet filters in different frequency and orientation domains. Then based on the response of filters, the optimal filter is selected among the filter bank. Considering the industrial requirement for finding adaptive solutions that can be executed in real time and reduce false rate, we use morphological analysis as an adaptive threshold technique for detection. By applying morphological analysis on response of the optimal filter, the defects are detected. The experimental results on different type of textiles show that the developed algorithm is robust, scalable and effective for detection various kind of textile defects.

David K. Hoffman - One of the best experts on this subject based on the ideXlab platform.

  • Shannon–Gabor Wavelet distributed approximating functional
    Chemical Physics Letters, 1998
    Co-Authors: David K. Hoffman, G.w. Wei, D. S. Zhang, Donald J. Kouri
    Abstract:

    Abstract The Shannon sampling theorem is critically reviewed from a physical point of view. An approximate sampling formula is proposed, combining Shannon sampling with a Gabor-distributed approximating functional (DAF) window function, which results in new Shannon–Gabor Wavelet DAFs (SGWDs). They are extremely smooth, decay rapidly, have simultaneous time-frequency localization, and are also generalized delta sequences (reducing to the Dirac delta function under the limit of a zero window width). Shannon's sampling theorem is recovered exactly when the window is infinitely wide.Finally, SGWDs are well-behaved L 2 ( R ) kernels, and thus can be used for solving differential equations.

  • shannon Gabor Wavelet distributed approximating functional
    Chemical Physics Letters, 1998
    Co-Authors: David K. Hoffman, G.w. Wei, D. S. Zhang, Donald J. Kouri
    Abstract:

    Abstract The Shannon sampling theorem is critically reviewed from a physical point of view. An approximate sampling formula is proposed, combining Shannon sampling with a Gabor-distributed approximating functional (DAF) window function, which results in new Shannon–Gabor Wavelet DAFs (SGWDs). They are extremely smooth, decay rapidly, have simultaneous time-frequency localization, and are also generalized delta sequences (reducing to the Dirac delta function under the limit of a zero window width). Shannon's sampling theorem is recovered exactly when the window is infinitely wide.Finally, SGWDs are well-behaved L 2 ( R ) kernels, and thus can be used for solving differential equations.

Fuji Ren - One of the best experts on this subject based on the ideXlab platform.

  • facial expression recognition based on Gabor Wavelet transform and histogram of oriented gradients
    International Conference on Mechatronics and Automation, 2015
    Co-Authors: Changqin Quan, Fuji Ren
    Abstract:

    In order to get more effective expression features, this paper proposes an approach based on Gabor feature and Histogram of Oriented Gradients (HOG). Gabor Wavelet filter is first used as preprocessing stage for feature extraction. Handing the characteristics with a large number of dimensions, binary encoding (BC) is applied for dimensionality reduction. Dimensionality of the feature vector is reduced by using HOG algorithm. Experiments were performed on Cohn-Kanade facial expression database and the support vector machine classifier is used for expression classification. We obtained experimental results with an average recognition rate of 92.5%, which reveals that the proposed method is superior to other Gabor Wavelet transform based approaches under the same experimental environment.