The Experts below are selected from a list of 1356 Experts worldwide ranked by ideXlab platform
Hitoshi Kiya - One of the best experts on this subject based on the ideXlab platform.
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Sparse Modeling on Distributed Encryption Data
ICASSP 2020 - 2020 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2020Co-Authors: Yukihiro Bandoh, Takayuki Nakachi, Hitoshi KiyaAbstract:Big-data analysis by edge/cloud systems is becoming more important. However, when information may lead to personal identification, such information tends to be encrypted and restricted to its owners to ensure privacy protection. The resulting data is often insufficiently detailed to permit useful analysis. As a result, the desired analysis accuracy may not be achieved. To deal with this issue, several studies have examined encryptions based on the random Unitary Transform. This is because the random Unitary Transform has lower computational complexity than other encryption schemes, and its encryption domain supports several signal processing algorithms. However, analysis models on distributed encrypted data, have not been studied deeply enough. In this paper, we construct an analysis model for data encrypted with the random Unitary Transform by deriving a LASSO solution for encrypted data. The analytical model can derive the same LASSO solution as that yielded by processing the original data (i.e. without encryption). The analytical model supports distributed encryption, where a data set consists of different components that are encrypted at different sites independently. The collaboration enables us to improve the accuracy of analysis for distributed privacy-sensitive information.
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Secure Dictionary Learning for Sparse Representation
2019 27th European Signal Processing Conference (EUSIPCO), 2019Co-Authors: Takayuki Nakachi, Yukihiro Bandoh, Hitoshi KiyaAbstract:In this paper, we propose secure dictionary learning for sparse representation based on a random Unitary Transform. Edge cloud computing is now spreading to many application fields including services that use sparse coding. This situation raises many new privacy concerns. The proposed scheme provides practical MOD and K-SVD schemes that allow computation on encrypted signals. We prove, theoretically, that the proposal has exactly the same dictionary and sparse coefficient estimation performance as sparse dictionary learning for unencrypted signals. It can be directly carried out by using MOD and K-SVD algorithms. Moreover, we apply it to image modeling based on an image patch model. Finally, we demonstrate its excellent performance on synthetic data and natural images.
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An Efficient Random Unitary Matrix for Biometric Template Protection
2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Syst, 2016Co-Authors: Yuko Saito, Ibuki Nakamura, Sayaka Shiota, Hitoshi KiyaAbstract:This paper proposes a new way to generate random Unitary matrices for biometric template protection. It is well known that the Unitary Transform-based template protection that is a class of cancelable biometrics systems, has some desirable properties such as being applicable to l2-norm minimization problems. However, its performance and effectiveness depend on the variety of a Unitary matrix. The aim of this paper is to generate an effective random Unitary matrix and evaluate the effectiveness in terms of security, recognition performance and the complexity of the recognition system. The proposed random matrix consists of a random permutation matrix and a Unitary matrix in which all elements have fixed values as the discrete Fourier Transform(DFT). It is also applied to face recognition experiments to demonstrate the effectiveness.
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EUSIPCO - Unitary Transform-based template protection and its properties
2015 23rd European Signal Processing Conference (EUSIPCO), 2015Co-Authors: Ibuki Nakamura, Yoshihide Tonomura, Hitoshi KiyaAbstract:We focus on the feature Transform approach as one methodology for biometric template protection, where the template consists of the features extracted from the biometric trait. This paper considers some properties of the Unitary Transform-based template protection in particular. It is known that the Euclidean distance between the templates protected by a Unitary Transform is the same as that between original (non-protected) ones as a property. In this paper, moreover, it is shown that it provides the same results in l 2 -norm minimization problems as those of original templates. This means that there is no degradation of recognition performance in authentication systems using l 2 -norm minimization. Therefore, the protected templates can be reissued multiple times without original templates. In addition, a DFT-based template protection scheme is proposed as an Unitary Transform-based one. The proposed scheme enables to efficiently generate protected templates by the FFT, in addition to the useful properties. It is also applied to face recognition experiments to evaluate the effectiveness.
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Unitary Transform-based template protection and its properties
2015 23rd European Signal Processing Conference (EUSIPCO), 2015Co-Authors: Ibuki Nakamura, Yoshihide Tonomura, Hitoshi KiyaAbstract:We focus on the feature Transform approach as one methodology for biometric template protection, where the template consists of the features extracted from the biometric trait. This paper considers some properties of the Unitary Transform-based template protection in particular. It is known that the Euclidean distance between the templates protected by a Unitary Transform is the same as that between original (non-protected) ones as a property. In this paper, moreover, it is shown that it provides the same results in l2-norm minimization problems as those of original templates. This means that there is no degradation of recognition performance in authentication systems using l2-norm minimization. Therefore, the protected templates can be reissued multiple times without original templates. In addition, a DFT-based template protection scheme is proposed as an Unitary Transform-based one. The proposed scheme enables to efficiently generate protected templates by the FFT, in addition to the useful properties. It is also applied to face recognition experiments to evaluate the effectiveness.
Erik Stauffer - One of the best experts on this subject based on the ideXlab platform.
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low complexity multi stream space time codes part ii Unitary Transform codes
IEEE Transactions on Communications, 2012Co-Authors: Bertrand Hochwald, Erik StaufferAbstract:We examine the design of space-time codes that allow simple encoding and decoding of high and low-priority streams of data. This paper comprises two parts. In the first part we introduce the system model, establish performance and complexity criteria, and introduce "direct-sum" codes that combine existing space-time codes with hierarchical modulation. In this second part, we show that the direct-sum codes of the first part can be greatly improved upon by non-direct-sum designs. We demonstrate Unitary-Transform\/ codes for two and four antennas. In particular, one such code performs 4 dB better than the direct-sum Alamouti code, with per-bit decoding complexity on one stream that is a bounded function of the rate of the other stream.
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Low-Complexity Multi-Stream Space-Time Codes—Part II: Unitary-Transform Codes
IEEE Transactions on Communications, 2012Co-Authors: Bertrand Hochwald, Erik StaufferAbstract:We examine the design of space-time codes that allow simple encoding and decoding of high and low-priority streams of data. This paper comprises two parts. In the first part we introduce the system model, establish performance and complexity criteria, and introduce "direct-sum" codes that combine existing space-time codes with hierarchical modulation. In this second part, we show that the direct-sum codes of the first part can be greatly improved upon by non-direct-sum designs. We demonstrate Unitary-Transform\/ codes for two and four antennas. In particular, one such code performs 4 dB better than the direct-sum Alamouti code, with per-bit decoding complexity on one stream that is a bounded function of the rate of the other stream.
Y. Yamashita - One of the best experts on this subject based on the ideXlab platform.
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Variable-length lapped Transforms with a combination of multiple synthesis filter banks for image coding
IEEE Transactions on Image Processing, 2006Co-Authors: T. Tanaka, Y. Hirasawa, Y. YamashitaAbstract:A class of lapped Transforms for image coding, which are characterized by variable-length synthesis filters, is introduced. In this class, the synthesis filter bank (FB) is first defined with an arbitrary combination of finite impulse response synthesis filters of perfect reconstruction FBs. An analysis FB is then obtained using direct matrix inversion or iterative implementation of Neumann series expansion. Moreover, to improve compression, we introduce a Unitary Transform that follows the analysis FB. This class enables a greater freedom of design than previously presented variable-length lapped Transforms. We illustrate several design examples and present experimental results for image coding, which indicate that the proposed Transforms are promising and comparable with conventional subband Transforms including wavelets.
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A novel class of variable-length lapped Transform for image coding
Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), 2003Co-Authors: T. Tanaka, Y. Hirasawa, Y. YamashitaAbstract:The theory and design for a novel class of a variable-length lapped Transform are presented. In this class, the synthesis filter bank is firstly defined with arbitrary combination of FIR filters, giving much freedom of design compared to previously presented variable-length lapped Transforms. The analysis filter bank is then obtained as the inverse of the synthesis bank by the Neumann series expansion to achieve the perfect reconstruction. Moreover, by introducing a Unitary Transform, we improve the compression performance of the analysis bank. We provide several design examples and experimental results of image coding, which show that the proposed Transform is promising and comparable with conventional subband Transforms including wavelets.
Jian-wei Yang - One of the best experts on this subject based on the ideXlab platform.
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shift Unitary Transform for constructing two dimensional wavelet filters
Journal of Applied Mathematics, 2011Co-Authors: Fei Li, Jian-wei YangAbstract:Due to the difficulty for constructing two-dimensional wavelet filters, the commonly used wavelet filters are tensor-product of one-dimensional wavelet filters. In some applications, more perfect reconstruction filters should be provided. In this paper, we introduce a Transformation which is referred to as Shift Unitary Transform (SUT) of Conjugate Quadrature Filter (CQF). In terms of this Transformation, we propose a parametrization method for constructing two-dimensional orthogonal wavelet filters. It is proved that tensor-product wavelet filters are only special cases of this parametrization method. To show this, we introduce the SUT of one-dimensional CQF and present a complete parametrization of one-dimensional wavelet system. As a result, more ways are provided to randomly generate two-dimensional perfect reconstruction filters.
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IAS - A Watermarking Scheme Based on Two-dimensional Wavelet Filter Parametrization
2009 Fifth International Conference on Information Assurance and Security, 2009Co-Authors: Guosheng Cheng, Jian-wei YangAbstract:In this paper, a parametrization of two-dimensional wavelet filter system is used as a method to protect wavelet-based watermarks against unauthorized detection. This system is developed in terms of a novel Transformation-Shift Unitary Transform (SUT) of Conjugate Quadrature filter (CQF). The commonly used wavelet filters are only special cases of this system. Based on this system, a watermarking scheme is described to embed watermark into low frequency sub-bands of wavelet Transformation. We overcome degradation problem by performing median filtering to the lowest frequency sub-band of wavelet Transform and embed watermark into visually insensitive locations. Experiments show this method is robust to compression,median-filtering etc.
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A Watermarking Scheme Based on Two-dimensional Wavelet Filter Parametrization
2009 Fifth International Conference on Information Assurance and Security, 2009Co-Authors: Guosheng Cheng, Jian-wei YangAbstract:In this paper, a parametrization of two-dimensional wavelet filter system is used as a method to protect wavelet-based watermarks against unauthorized detection. This system is developed in terms of a novel Transformation-shift Unitary Transform (SUT) of conjugate quadrature filter (CQF). The commonly used wavelet filters are only special cases of this system. Based on this system, a watermarking scheme is described to embed watermark into low frequency sub-bands of wavelet Transformation. We overcome degradation problem by performing median filtering to the lowest frequency sub-band of wavelet Transform and embed watermark into visually insensitive locations. Experiments show this method is robust to compression,median-filtering etc.
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Parametrization construction of two-dimensional wavelet filters
2007 International Conference on Wavelet Analysis and Pattern Recognition, 2007Co-Authors: Jian-wei Yang, Guosheng Cheng, Y.y. TangAbstract:In this paper, a Transformation that we refer to as shift Unitary Transform (SUT) of conjugate quadrature filter (CQF) is proposed. In terms of this Transformation, we present a parametrization method for constructing two-dimensional orthogonal wavelet filters. It is proved that tensor-product wavelet filters are only special cases of this method. Therefore, more ways are provided to randomly generate perfect reconstruction filters. Nonseparable wavelet filters are derived by this method, and applied to a blind watermarking scheme. Experimental results show that watermarking scheme based on these filters is more resistant to sharpening than scheme based on tensor-product wavelet filters.
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Two-Dimensional Wavelet Filters for Watermarking
2007 International Conference on Computational Intelligence and Security (CIS 2007), 2007Co-Authors: Jian-wei Yang, Wenbing Chen, Guosheng ChengAbstract:Discrete non-separable wavelet Transform (DNWT) re- veals more features than discrete separable wavelet trans- form (DSWT) does. We propose to embed watermark by DNWT. To construct non-separable wavelet filters, we intro- duce a novel Transformation shift Unitary Transform (SUT) of conjugate quadrature filter (CQF). Based on this transfor- mation, a parametrization construction of two-dimensional wavelet filters is provided. Non-separable wavelet filters derived by this method are applied to a blind watermark- ing scheme. Experimental results show that watermarking scheme based on these filters is more resistant to sharpen- ing than watermarking scheme based on separable wavelet filters does.
Xile Zhao - One of the best experts on this subject based on the ideXlab platform.
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patched tubes Unitary Transform for robust tensor completion
Pattern Recognition, 2020Co-Authors: Michael K Ng, Xiongjun Zhang, Xile ZhaoAbstract:Abstract The aim of the robust tensor completion problem for third-order tensors is to recover a low-rank tensor from incomplete and/or corrupted observations. In this paper, we develop a patched-tubes Unitary Transform method for robust tensor completion. The proposed method is to extract similar patched-tubes to form a third-order sub-tensor, and then a Transformed tensor singular value decomposition is employed to recover such low-rank incomplete and/or corrupted sub-tensor. Here the Unitary Transform matrix for Transformed tensor singular value decomposition is constructed by using left singular vectors of the unfolding matrix arising from such sub-tensor. Moreover, we establish the perturbation results of the Transformed tensor singular value decomposition for patched-tubes tensor completion. Extensive numerical experiments on hyperspectral, video and face data sets are presented to demonstrate the superior performance of the proposed patched-tubes Unitary Transform method over testing state-of-the-art robust tensor completion methods.
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Patched-tube Unitary Transform for robust tensor completion
Pattern Recognition, 2020Co-Authors: Michael K Ng, Xiongjun Zhang, Xile ZhaoAbstract:Abstract The aim of the robust tensor completion problem for third-order tensors is to recover a low-rank tensor from incomplete and/or corrupted observations. In this paper, we develop a patched-tubes Unitary Transform method for robust tensor completion. The proposed method is to extract similar patched-tubes to form a third-order sub-tensor, and then a Transformed tensor singular value decomposition is employed to recover such low-rank incomplete and/or corrupted sub-tensor. Here the Unitary Transform matrix for Transformed tensor singular value decomposition is constructed by using left singular vectors of the unfolding matrix arising from such sub-tensor. Moreover, we establish the perturbation results of the Transformed tensor singular value decomposition for patched-tubes tensor completion. Extensive numerical experiments on hyperspectral, video and face data sets are presented to demonstrate the superior performance of the proposed patched-tubes Unitary Transform method over testing state-of-the-art robust tensor completion methods.
