The Experts below are selected from a list of 4173 Experts worldwide ranked by ideXlab platform
Raghunath S Holambe - One of the best experts on this subject based on the ideXlab platform.
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text independent speaker identification using radon and discrete Cosine Transforms based features from speech spectrogram
Pattern Recognition, 2011Co-Authors: Pawan K Ajmera, Dattatray V Jadhav, Raghunath S HolambeAbstract:This paper presents a new feature extraction technique for speaker recognition using Radon transform (RT) and discrete Cosine transform (DCT). The spectrogram is compact, efficient in representation and carries information about acoustic features in the form of pattern. In the proposed method, speaker specific features have been extracted by applying image processing techniques to the pattern available in the spectrogram. Radon transform has been used to derive the effective acoustic features from the speech spectrogram. Radon transform adds up the pixel values in the given image along a straight line in a particular direction and at a specific displacement. The proposed technique computes Radon projections for seven orientations and captures the acoustic characteristics of the spectrogram. DCT applied on Radon projections yields low dimensional feature vector. The technique is computationally efficient, text-independent, robust to session variations and insensitive to additive noise. The performance of the proposed algorithm has been evaluated using the Texas Instruments and Massachusetts Institute of Technology (TIMIT) and our own created Shri Guru Gobind Singhji (SGGS) databases. The recognition rate of the proposed algorithm on TIMIT database (consisting of 630 speakers) is 96.69% and for SGGS database (consisting of 151 speakers) is 98.41%. These results highlight the superiority of the proposed method over some of the existing algorithms.
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rotation illumination invariant polynomial kernel fisher discriminant analysis using radon and discrete Cosine Transforms based features for face recognition
Pattern Recognition Letters, 2010Co-Authors: Dattatray V Jadhav, Raghunath S HolambeAbstract:This paper presents an in-plane rotation (tilt), illumination invariant pattern recognition framework based on the combination of the features extracted using Radon and discrete Cosine Transforms and kernel based learning for face recognition. The use of Radon transform enhances the low frequency components, which are useful for face recognition and that of DCT yields low dimensional feature vector. The proposed technique computes Radon projections in different orientations and captures the directional features of the face images. DCT applied on Radon projections provides frequency features. Further, polynomial kernel Fisher discriminant analysis implemented on these features enhances discrimination capability of these features. The technique is also robust to zero mean white noise. The feasibility of the proposed technique has been evaluated using FERET, ORL, and Yale databases.
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fast communication radon and discrete Cosine Transforms based feature extraction and dimensionality reduction approach for face recognition
Signal Processing, 2008Co-Authors: Dattatray V Jadhav, Raghunath S HolambeAbstract:This paper presents a pattern recognition framework for face recognition based on the combination of Radon and discrete Cosine Transforms (DCT). The property of Radon transform to enhance the low frequency components, which are useful for face recognition, has been exploited to derive the effective facial features. Data compaction property of DCT yields lower-dimensional feature vector. The proposed technique computes Radon projections in different orientations and captures the directional features of the face images. Further, DCT applied on Radon projections provides frequency features. The technique is invariant to in-plane rotation (tilt) and robust to zero mean white noise. The proposed algorithm is evaluated using FERET and ORL databases. The experimental results show the superiority of the proposed method compared to some of the existing algorithms.
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fast communication radon and discrete Cosine Transforms based feature extraction and dimensionality reduction approach for face recognition
Signal Processing, 2008Co-Authors: Dattatray V Jadhav, Raghunath S HolambeAbstract:This paper presents a pattern recognition framework for face recognition based on the combination of Radon and discrete Cosine Transforms (DCT). The property of Radon transform to enhance the low frequency components, which are useful for face recognition, has been exploited to derive the effective facial features. Data compaction property of DCT yields lower-dimensional feature vector. The proposed technique computes Radon projections in different orientations and captures the directional features of the face images. Further, DCT applied on Radon projections provides frequency features. The technique is invariant to in-plane rotation (tilt) and robust to zero mean white noise. The proposed algorithm is evaluated using FERET and ORL databases. The experimental results show the superiority of the proposed method compared to some of the existing algorithms.
Anand Asundi - One of the best experts on this subject based on the ideXlab platform.
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phase retrieval with the transport of intensity equation in an arbitrarily shaped aperture by iterative discrete Cosine Transforms
Optics Letters, 2015Co-Authors: Lei Huang, Mourad Idir, Chao Zuo, Anand AsundiAbstract:A transport-of-intensity equation (TIE)-based phase retrieval method is proposed with putting an arbitrarily shaped aperture into the optical wavefield. In this arbitrarily shaped aperture, the TIE can be solved under nonuniform illuminations and even nonhomogeneous boundary conditions by iterative discrete Cosine Transforms with a phase compensation mechanism. Simulation with arbitrary phase, arbitrary aperture shape, and nonuniform intensity distribution verifies the effective compensation and high accuracy of the proposed method. Experiment is also carried out to check the feasibility of the proposed method in real measurement. Comparing to the existing methods, the proposed method is applicable for any types of phase distribution under nonuniform illumination and nonhomogeneous boundary conditions within an arbitrarily shaped aperture, which enables the technique of TIE with hard aperture to become a more flexible phase retrieval tool in practical measurements.
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shape reconstruction from gradient data in an arbitrarily shaped aperture by iterative discrete Cosine Transforms in southwell configuration
Optics and Lasers in Engineering, 2015Co-Authors: Lei Huang, Mourad Idir, Chao Zuo, Konstantine Kaznatcheev, Lin Zhou, Anand AsundiAbstract:The shape reconstruction from gradient data is a common problem in many slope-based metrology applications. In practice, the gradient data may not be ideally available for the whole field of view as expected, due to the aperture or the unmeasurable part of sample. An iterative method by using discrete Cosine Transforms is addressed in this work to deal with the integration problem with incomplete gradient dataset in Southwell configuration. Simulation indicates that the discrete Cosine transform provides better initial values than discrete Fourier transform does, and it converges to a more accurate level by updating with spectrum-based slopes comparing to the slope updates from finite difference in classical method. Experimental results show the feasibility of the proposed approach in a practical measurement.
Bing Zeng - One of the best experts on this subject based on the ideXlab platform.
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directional discrete Cosine Transforms a new framework for image coding
IEEE Transactions on Circuits and Systems for Video Technology, 2008Co-Authors: Bing Zeng, Jingjing FuAbstract:Nearly all block-based transform schemes for image and video coding developed so far choose the 2-D discrete Cosine transform (DCT) of a square block shape. With almost no exception, this conventional DCT is implemented separately through two 1-D Transforms, one along the vertical direction and another along the horizontal direction. In this paper, we develop a new block-based DCT framework in which the first transform may choose to follow a direction other than the vertical or horizontal one. The coefficients produced by all directional Transforms in the first step are arranged appropriately so that the second transform can be applied to the coefficients that are best aligned with each other. Compared with the conventional DCT, the resulting directional DCT framework is able to provide a better coding performance for image blocks that contain directional edges-a popular scenario in many image signals. By choosing the best from all directional DCTs (including the conventional DCT as a special case) for each image block, we will demonstrate that the rate-distortion coding performance can be improved remarkably. Finally, a brief theoretical analysis is presented to justify why certain coding gain (over the conventional DCT) results from this directional framework.
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directional discrete Cosine Transforms a theoretical analysis
International Conference on Acoustics Speech and Signal Processing, 2007Co-Authors: Bing ZengAbstract:Nearly all block-based transform techniques developed so far for image and video coding applications choose the 2-D discrete Cosine transform (DCT) of a square block shape. With almost no exception, this conventional DCT is always implemented separately through two 1-D Transforms, along the vertical and horizontal directions, respectively. In one of our recent works, we have developed a directional DCT framework in which the first transform may choose to follow a direction other than the vertical or horizontal one, while the second transform is arranged to be a horizontal one. Compared to the conventional DCT, our directional DCT framework has been demonstrated to provide a better coding performance for image blocks that contain directional edges - a popular scenario in many image and video signals. In this paper, we attempt to pursue an in-depth theoretical analysis to understand how the coding gain is produced in the directional DCTframework and how big it can be.
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diagonal discrete Cosine Transforms for image coding
Advances in Multimedia, 2006Co-Authors: Bing ZengAbstract:A new block-based DCT framework has been developed recently in[1] in which the first transform may choose to follow a direction other than the vertical or horizontal one – the default direction in the conventional DCT. In this paper, we focus on two diagonal directions because they are visually more important than other directions in an image block (except the vertical and horizontal ones). Specifically, we re-formulate the framework of two diagonal DCTs and use them in combination with the conventional DCT. We will discuss issues such as the directional mode selection and the cross-check of directional modes. Some experimental results are provided to demonstrate the effectiveness of our proposed diagonal DCT’s in image coding applications.
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directional discrete Cosine Transforms for image coding
International Conference on Multimedia and Expo, 2006Co-Authors: Bing ZengAbstract:Nearly all block-based transform schemes for image and video coding developed so far choose the 2-D discrete Cosine transform (DCT) of a square block shape. With almost no exception, this conventional DCT is implemented separately through two 1-D Transforms, one along the vertical direction and another along the horizontal direction. In this paper, we develop a new block-based DCT framework in which the first transform may follow a direction other than the vertical or horizontal one, while the second transform is arranged to be a horizontal one. Compared to the conventional DCT, the resulting directional DCT framework is able to provide a better coding performance for image blocks that contain directional edges - a popular scenario in many image signals. By choosing the best from all directional DCT's (including the conventional DCT as a special case) for each image block, we will demonstrate that the rate-distortion coding performance can be improved remarkably.
Dattatray V Jadhav - One of the best experts on this subject based on the ideXlab platform.
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text independent speaker identification using radon and discrete Cosine Transforms based features from speech spectrogram
Pattern Recognition, 2011Co-Authors: Pawan K Ajmera, Dattatray V Jadhav, Raghunath S HolambeAbstract:This paper presents a new feature extraction technique for speaker recognition using Radon transform (RT) and discrete Cosine transform (DCT). The spectrogram is compact, efficient in representation and carries information about acoustic features in the form of pattern. In the proposed method, speaker specific features have been extracted by applying image processing techniques to the pattern available in the spectrogram. Radon transform has been used to derive the effective acoustic features from the speech spectrogram. Radon transform adds up the pixel values in the given image along a straight line in a particular direction and at a specific displacement. The proposed technique computes Radon projections for seven orientations and captures the acoustic characteristics of the spectrogram. DCT applied on Radon projections yields low dimensional feature vector. The technique is computationally efficient, text-independent, robust to session variations and insensitive to additive noise. The performance of the proposed algorithm has been evaluated using the Texas Instruments and Massachusetts Institute of Technology (TIMIT) and our own created Shri Guru Gobind Singhji (SGGS) databases. The recognition rate of the proposed algorithm on TIMIT database (consisting of 630 speakers) is 96.69% and for SGGS database (consisting of 151 speakers) is 98.41%. These results highlight the superiority of the proposed method over some of the existing algorithms.
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rotation illumination invariant polynomial kernel fisher discriminant analysis using radon and discrete Cosine Transforms based features for face recognition
Pattern Recognition Letters, 2010Co-Authors: Dattatray V Jadhav, Raghunath S HolambeAbstract:This paper presents an in-plane rotation (tilt), illumination invariant pattern recognition framework based on the combination of the features extracted using Radon and discrete Cosine Transforms and kernel based learning for face recognition. The use of Radon transform enhances the low frequency components, which are useful for face recognition and that of DCT yields low dimensional feature vector. The proposed technique computes Radon projections in different orientations and captures the directional features of the face images. DCT applied on Radon projections provides frequency features. Further, polynomial kernel Fisher discriminant analysis implemented on these features enhances discrimination capability of these features. The technique is also robust to zero mean white noise. The feasibility of the proposed technique has been evaluated using FERET, ORL, and Yale databases.
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fast communication radon and discrete Cosine Transforms based feature extraction and dimensionality reduction approach for face recognition
Signal Processing, 2008Co-Authors: Dattatray V Jadhav, Raghunath S HolambeAbstract:This paper presents a pattern recognition framework for face recognition based on the combination of Radon and discrete Cosine Transforms (DCT). The property of Radon transform to enhance the low frequency components, which are useful for face recognition, has been exploited to derive the effective facial features. Data compaction property of DCT yields lower-dimensional feature vector. The proposed technique computes Radon projections in different orientations and captures the directional features of the face images. Further, DCT applied on Radon projections provides frequency features. The technique is invariant to in-plane rotation (tilt) and robust to zero mean white noise. The proposed algorithm is evaluated using FERET and ORL databases. The experimental results show the superiority of the proposed method compared to some of the existing algorithms.
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fast communication radon and discrete Cosine Transforms based feature extraction and dimensionality reduction approach for face recognition
Signal Processing, 2008Co-Authors: Dattatray V Jadhav, Raghunath S HolambeAbstract:This paper presents a pattern recognition framework for face recognition based on the combination of Radon and discrete Cosine Transforms (DCT). The property of Radon transform to enhance the low frequency components, which are useful for face recognition, has been exploited to derive the effective facial features. Data compaction property of DCT yields lower-dimensional feature vector. The proposed technique computes Radon projections in different orientations and captures the directional features of the face images. Further, DCT applied on Radon projections provides frequency features. The technique is invariant to in-plane rotation (tilt) and robust to zero mean white noise. The proposed algorithm is evaluated using FERET and ORL databases. The experimental results show the superiority of the proposed method compared to some of the existing algorithms.
Boris Rubin - One of the best experts on this subject based on the ideXlab platform.
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the fourier transform approach to inversion of lambda Cosine and funk Transforms on the unit sphere
arXiv: Functional Analysis, 2020Co-Authors: Boris RubinAbstract:We use the classical Fourier analysis to introduce analytic families of weighted differential operators on the unit sphere. These operators are polynomial functions of the usual Beltrami-Laplace operator. New inversion formulas are obtained for totally geodesic Funk Transforms on the sphere and the correpsonding lambda-Cosine Transforms.
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the λ Cosine Transforms with odd kernel and the hemispherical transform
Fractional Calculus and Applied Analysis, 2014Co-Authors: Boris RubinAbstract:We review some basic facts about the λ-Cosine Transforms with odd kernel on the unit sphere Sn−1 in ℝn. These Transforms are represented by the spherical fractional integrals arising as a result of evaluation of the Fourier transform of homogeneous functions. The related topic is the hemispherical transform which assigns to every finite Borel measure on Sn−1 its values for all hemispheres. We revisit the known facts about this transform and obtain new results. In particular, we show that the classical Funk- Radon-Helgason inversion method of spherical means is applicable to the hemispherical transform of Lp-functions.
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Intersection bodies and generalized Cosine Transforms
Advances in Mathematics, 2008Co-Authors: Boris RubinAbstract:The paper is focused on intimate connection between geometric properties of intersection bodies in convex geometry and generalized Cosine Transforms in harmonic analysis. A new concept of ?-intersection body, that unifies some known classes of geometric objects, is introduced. A parallel between trace theorems in function theory, restriction onto lower-dimensional subspaces of the spherical Radon Transforms and the generalized Cosine Transforms, and sections of ?-intersection bodies is established. New integral formulas for different classes of Cosine Transforms are obtained and examples of ?-intersection bodies are given. We also revisit some known facts in this area and give them new simple proofs
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Intersection Bodies and Generalized Cosine Transforms
arXiv: Functional Analysis, 2007Co-Authors: Boris RubinAbstract:Intersection bodies represent a remarkable class of geometric objects associated with sections of star bodies and invoking Radon Transforms, generalized Cosine Transforms, and the relevant Fourier analysis. The main focus of this article is interrelation between generalized Cosine Transforms of different kinds in the context of their application to investigation of a certain family of intersection bodies, which we call $\lam$-intersection bodies. The latter include $k$-intersection bodies (in the sense of A. Koldobsky) and unit balls of finite-dimensional subspaces of $L_p$-spaces. In particular, we show that restrictions onto lower dimensional subspaces of the spherical Radon Transforms and the generalized Cosine Transforms preserve their integral-geometric structure. We apply this result to the study of sections of $\lam$-intersection bodies. New characterizations of this class of bodies are obtained and examples are given. We also review some known facts and give them new proofs.
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Composite Cosine Transforms
arXiv: Functional Analysis, 2006Co-Authors: E. Ournycheva, Boris RubinAbstract:The Cosine Transforms of functions on the unit sphere play an important role in convex geometry, the Banach space theory, stochastic geometry and other areas. Their higher-rank generalization to Grassmann manifolds represents an interesting mathematical object useful for applications. We introduce more general integral Transforms that reveal distinctive features of higher-rank objects in full generality. We call these new Transforms the composite Cosine Transforms, by taking into account that their kernels agree with the composite power function of the cone of positive definite symmetric matrices. We show that injectivity of the composite Cosine Transforms can be studied using standard tools of the Fourier analysis on matrix spaces. In the framework of this approach, we introduce associated generalized zeta integrals and give new simple proofs to the relevant functional relations. Our technique is based on application of the higher-rank Radon transform on matrix spaces.
