The Experts below are selected from a list of 81 Experts worldwide ranked by ideXlab platform

Alessandro Neri - One of the best experts on this subject based on the ideXlab platform.

  • a Commutative digital image watermarking and encryption method in the tree structured haar transform domain
    Signal Processing-image Communication, 2011
    Co-Authors: Michela Cancellaro, Francesco G.b. De Natale, Federica Battisti, Marco Carli, Giulia Boato, Alessandro Neri
    Abstract:

    In this paper a Commutative watermarking and ciphering scheme for digital images is presented. The Commutative Property of the proposed method allows to cipher a watermarked image without interfering with the embedded signal or to watermark an encrypted image still allowing a perfect deciphering. Both operations are performed on a parametric transform domain: the Tree Structured Haar transform. The key dependence of the adopted transform domain increases the security of the overall system. In fact, without the knowledge of the generating key it is not possible to extract any useful information from the ciphered-watermarked image. Experimental results show the effectiveness of the proposed scheme.

  • a joint digital watermarking and encryption method
    electronic imaging, 2008
    Co-Authors: Michela Cancellaro, Francesco G.b. De Natale, Federica Battisti, Marco Carli, Giulia Boato, Alessandro Neri
    Abstract:

    In this paper a joint watermarking and ciphering scheme for digital images is presented. Both operations are performed on a key-dependent transform domain. The Commutative Property of the proposed method allows to cipher a watermarked image without interfering with the embedded signal or to watermark an encrypted image still allowing a perfect deciphering. Furthermore, the key dependence of the transform domain increases the security of the overall system. Experimental results show the effectiveness of the proposed scheme.

Michele Caputo - One of the best experts on this subject based on the ideXlab platform.

  • Commutative and associative properties of the caputo fractional derivative and its generalizing convolution operator
    Communications in Nonlinear Science and Numerical Simulation, 2020
    Co-Authors: Luisa Beghin, Michele Caputo
    Abstract:

    Abstract While for the integer-order derivatives, the Commutative and semigroup (or associative) properties hold, the same is not true, in general, for the fractional derivatives. We show that, when the function is analytic, the Caputo derivative enjoys the above mentioned properties, at least when the fractional indices are smaller than one. This result is proved under assumptions on the derivatives (evaluated in zero) that are much less restrictive than the usual requirement of vanishing in the origin. Finally, we study the same properties for a generalization of the above fractional derivative, i.e. the Caputo-type convolution operator defined in [12] and [25]. In this more general setting (which includes the fractional, as particular case), we prove that the Commutative Property holds, while the associative Property must be formulated accordingly.

Michela Cancellaro - One of the best experts on this subject based on the ideXlab platform.

  • a Commutative digital image watermarking and encryption method in the tree structured haar transform domain
    Signal Processing-image Communication, 2011
    Co-Authors: Michela Cancellaro, Francesco G.b. De Natale, Federica Battisti, Marco Carli, Giulia Boato, Alessandro Neri
    Abstract:

    In this paper a Commutative watermarking and ciphering scheme for digital images is presented. The Commutative Property of the proposed method allows to cipher a watermarked image without interfering with the embedded signal or to watermark an encrypted image still allowing a perfect deciphering. Both operations are performed on a parametric transform domain: the Tree Structured Haar transform. The key dependence of the adopted transform domain increases the security of the overall system. In fact, without the knowledge of the generating key it is not possible to extract any useful information from the ciphered-watermarked image. Experimental results show the effectiveness of the proposed scheme.

  • a joint digital watermarking and encryption method
    electronic imaging, 2008
    Co-Authors: Michela Cancellaro, Francesco G.b. De Natale, Federica Battisti, Marco Carli, Giulia Boato, Alessandro Neri
    Abstract:

    In this paper a joint watermarking and ciphering scheme for digital images is presented. Both operations are performed on a key-dependent transform domain. The Commutative Property of the proposed method allows to cipher a watermarked image without interfering with the embedded signal or to watermark an encrypted image still allowing a perfect deciphering. Furthermore, the key dependence of the transform domain increases the security of the overall system. Experimental results show the effectiveness of the proposed scheme.

Luisa Beghin - One of the best experts on this subject based on the ideXlab platform.

  • Commutative and associative properties of the caputo fractional derivative and its generalizing convolution operator
    Communications in Nonlinear Science and Numerical Simulation, 2020
    Co-Authors: Luisa Beghin, Michele Caputo
    Abstract:

    Abstract While for the integer-order derivatives, the Commutative and semigroup (or associative) properties hold, the same is not true, in general, for the fractional derivatives. We show that, when the function is analytic, the Caputo derivative enjoys the above mentioned properties, at least when the fractional indices are smaller than one. This result is proved under assumptions on the derivatives (evaluated in zero) that are much less restrictive than the usual requirement of vanishing in the origin. Finally, we study the same properties for a generalization of the above fractional derivative, i.e. the Caputo-type convolution operator defined in [12] and [25]. In this more general setting (which includes the fractional, as particular case), we prove that the Commutative Property holds, while the associative Property must be formulated accordingly.

Francesco G.b. De Natale - One of the best experts on this subject based on the ideXlab platform.

  • a Commutative digital image watermarking and encryption method in the tree structured haar transform domain
    Signal Processing-image Communication, 2011
    Co-Authors: Michela Cancellaro, Francesco G.b. De Natale, Federica Battisti, Marco Carli, Giulia Boato, Alessandro Neri
    Abstract:

    In this paper a Commutative watermarking and ciphering scheme for digital images is presented. The Commutative Property of the proposed method allows to cipher a watermarked image without interfering with the embedded signal or to watermark an encrypted image still allowing a perfect deciphering. Both operations are performed on a parametric transform domain: the Tree Structured Haar transform. The key dependence of the adopted transform domain increases the security of the overall system. In fact, without the knowledge of the generating key it is not possible to extract any useful information from the ciphered-watermarked image. Experimental results show the effectiveness of the proposed scheme.

  • a joint digital watermarking and encryption method
    electronic imaging, 2008
    Co-Authors: Michela Cancellaro, Francesco G.b. De Natale, Federica Battisti, Marco Carli, Giulia Boato, Alessandro Neri
    Abstract:

    In this paper a joint watermarking and ciphering scheme for digital images is presented. Both operations are performed on a key-dependent transform domain. The Commutative Property of the proposed method allows to cipher a watermarked image without interfering with the embedded signal or to watermark an encrypted image still allowing a perfect deciphering. Furthermore, the key dependence of the transform domain increases the security of the overall system. Experimental results show the effectiveness of the proposed scheme.