15 results about "Image hiding" patented technology

The invention discloses a completely reversible image steganography method based on a reversible neural network, and aims to improve the robustness, capacity and safety of image steganography. The method comprises the following steps: 1) obtaining a processed secret image S through N reversible blocks, and adding a carrier image and the processed secret image S; 2) in a steganography process, integrating a simulation attack layer, and obtaining an attacked secret-containing image by the secret-containing image through the simulation attack layer, so as to carry out confrontation optimization on network training; (3) the attacked secret-containing image is restored to be in a non-attacked state through a content enhancement module, a cover image is found in a receiver database, and a processed secret image S is obtained through subtraction of the cover image and the secret-carrying image; 4) inputting the processed secret image S into a reversible neural network to recover a secret image; and 5) the optimization strategy of the whole network is divided into the design of a training strategy and a loss function. Through the innovative architecture of the invention, the complete reversibility of image hiding and reconstruction is successfully realized.

The invention discloses an image hiding method based on a space-channel attention mechanism and a related device, and belongs to the technical field of image hiding. The method comprises the following steps: inputting a secret image and a carrier image into a pre-trained image hiding network model to obtain a secret-containing image and loss information, and completing image hiding; the image hiding network model is an image hiding network model based on a space-channel attention mechanism and comprises a preprocessing network, a hiding network and an extraction network; the hidden network takes a reversible neural network as a basic framework, forward propagation and reverse propagation processes of the reversible neural network are modeled as encoding and decoding processes of an image according to the requirement of an image steganography task, and reversible hiding and high-quality extraction of a secret image are realized in combination with DWT (Discrete Wavelet Transform).

An ultrasound diagnostic apparatus includes: an ultrasound probe that transmits an ultrasound wave and receives a reflected wave; a display that displays an ultrasound image on a screen; and a hardware processor that activates a screen saver processing of displaying an image hiding information displayed on the screen or a freeze processing of stopping transmission and reception of the ultrasound wave when conditions (A1) or (A2) is continuously satisfied for a predetermined time or more while the ultrasound image is displayed, wherein the conditions (A1) and (A2) are: (A1) a state in which, in an input captured image, a change amount of the probe and surroundings is a first threshold or less; and (A2) a state in which a volume of input voice is a second threshold or less, or a state in which a volume of a specific frequency of input sound is a third threshold or less.

The invention relates to the technical field of data security, and discloses an image hiding method and system based on a local binary pattern, and the method comprises the steps: calculating a texture feature matrix of the local binary pattern of a plaintext image; generating a three-dimensional chaotic sequence according to the texture feature matrix; constructing a measurement matrix by using the three-dimensional chaotic sequence; performing two-dimensional compressed sensing processing on the plaintext image by using the measurement matrix to obtain a measurement value matrix after the plaintext image is compressed; performing scrambling and diffusion operation on the measurement value matrix to obtain a ciphertext image; the ciphertext image is embedded into the carrier image to obtain the encrypted carrier image, so that the known plaintext attack can be effectively resisted, the imperceptibility of the encrypted carrier image is improved, the blind extraction effect can be realized, and the efficiency and security of image protection are greatly improved.

The invention discloses a remote sensing image hiding and recovering method and device based on space-frequency collaborative modeling. The method comprises the following steps: acquiring a to-be-hidden remote sensing image and a carrier image; inputting a to-be-hidden remote sensing image and a carrier image into the pre-embedded residual attention module to obtain condition features, and inputting the condition features into the image hiding network to obtain a secret-containing image; performing discrete wavelet transform on the secret-containing image to obtain a high-frequency feature and a low-frequency feature, and inputting the high-frequency feature and the low-frequency feature into a Gaussian cross-frequency fusion module to obtain a dynamic fusion feature; and inputting the dynamic fusion features into a reconstruction recovery module to obtain a secret image. According to the method, the fidelity, the robustness and the detection resistance of the secret image can be improved.

The invention belongs to the technical field of general image data processing, and particularly relates to an image hiding method and device based on a reversible neural network, and the method comprises the steps: obtaining a training image based on a common data set, and carrying out the preprocessing of the training image; acquiring a digital image to which a watermark needs to be added, and generating a two-dimensional code image with the same size as the digital image; constructing an LMFI network model framework; training an LMFI network model framework by using the preprocessed training image; the trained LMFI network model framework is utilized to process a digital image needing to be added with a watermark, and an image containing a hidden watermark is generated; and when watermark extraction needs to be carried out on the image with the hidden watermark, obtaining a recovered watermark image by using the trained LMFI network model framework. According to the method, a large amount of information can be hidden, meanwhile, low parameter quantity and high image quality are kept, and the method can be well suitable for the fields of digital image copyright protection and the like.

The invention provides a constructive image hiding method based on attribute conversion, and the method comprises the steps: 1, selecting two images with completely different styles as a reference image and a secret image respectively, deconstructing the reference image and the secret image at a hiding end, generating secret-containing content features through a content feature hiding network, and hiding the secret-containing content features in the hidden end; a secret-containing conversion image is further obtained through a generator; 2, the extraction end deconstructs the secret-containing image, obtains the content features of the secret image through a content feature extraction network, and further recovers the secret image through a generator; and step 3, designing an information hiding and image extraction loss function to train the frame until convergence. According to the method, image hiding can be realized while image conversion is carried out, and the method has important prospects and application values in the field of hidden transmission.

The application discloses an image hiding encryption method based on a bidirectional asymmetric nano-printing super surface, and comprises the following specific steps: 1) constructing a nano structure unit; 2) optimizing the structure parameters of two nano bricks through an electromagnetic simulation software according to a selected working wavelength λ; 3) constructing a nano structure array, setting linearly polarized light with a polarization direction α1=π / 2 to be incident on the nano structure array from the upper surface and the lower surface respectively and then passing through a polarizer with a transparent axis direction α2=π / 2, the image information displayed under the two incident conditions is consistent, and the first image can be encoded in the nano structure array; linearly polarized light with an unchanged polarization direction is incident on the nano structure array and then passes through a polarizer with a transparent axis direction α2=0, the image information displayed under the two incident conditions is different, and the second image can be encoded in the nano structure array by adding the two images pixel by pixel, thereby providing a method for image hiding encryption and improving the concealment of the image.

This invention discloses a reversible multi-image hiding method and apparatus based on upsampling. The method selects an appropriate upsampling rate to upsample the carrier image according to the size of the multiple secret images to be hidden, thereby obtaining a target image with sufficient hiding capacity. Common embedding algorithms are then used to hide the multiple images. This invention not only achieves simultaneous hiding of multiple secret images with high capacity but also improves the quality of the disguised image while ensuring lossless recovery of the multiple secret images.

The present invention belongs to the field of general image data processing technology, and specifically relates to an image hiding method and device based on a reversible neural network, the method comprising: obtaining a training image based on a public data set, and preprocessing the training image; obtaining a digital image to be watermarked, and generating a two-dimensional code image of the same size as the digital image; constructing an LMFI network model framework; using the preprocessed training image to train the LMFI network model framework; using the trained LMFI network model framework to process the digital image to be watermarked, and generating an image containing a hidden watermark; when it is necessary to extract the watermark from the image after the hidden watermark, using the trained LMFI network model framework to obtain a restored watermark image. The present invention can hide a large amount of information while maintaining a low parameter amount and a high image quality, and can be well applied to fields such as digital image copyright protection.

An information processing apparatus including a display control unit that causes an image captured by any of one or a plurality of imaging devices to be displayed in a captured image display region that is a part of a display unit, causes second information related to the one or plurality of imaging devices to be displayed in a captured image hiding region that is a part of the display unit and different from the captured image display region, and causes first information related to the one or plurality of corresponding imaging devices to be displayed in the captured image display region in accordance with the second information being displayed and the one or plurality of imaging devices being in a predetermined state.

The invention provides an image hiding method based on a restricted Boltzmann machine and parallel compressed sensing. The method comprises an encryption stage and an embedding stage. In the encryption stage, sparse decomposition, image scrambling and threshold processing are sequentially carried out on a plaintext image, then a measurement matrix is constructed by using a random sequence to carry out parallel compressed sensing, then quantization processing is carried out on the image, and further rotation scrambling and random diffusion are carried out to obtain a ciphertext image; in the embedding stage, ciphertext image information is embedded into different wavelet coefficients of a carrier image through lifting wavelet transformation, and the embedding depth is dynamically selected according to a random sequence, so that the concealment and the safety of the embedded information are improved; according to the method, the randomness of the sequence can be effectively improved, the image processing efficiency is greatly improved, and high-quality image reconstruction can be realized under a relatively low compression ratio; in addition, the encrypted image generated by the method is higher in anti-attack capability and robustness.

This invention relates to an image processing method, including image hiding steps: acquiring a carrier image and converting the carrier image to the frequency domain to obtain a carrier frequency image; acquiring a secret image and converting the secret image to the frequency domain to obtain a secret frequency image; concatenating the carrier frequency image and the secret frequency image to obtain a first concatenated image; performing n consecutive affine transformations on the first concatenated image, corresponding to each affine transformation to obtain n first affine transformed images; concatenating the n first affine transformed images and performing an affine transformation to obtain a second affine transformed image; performing channel compression on the second affine transformed image to obtain a first compressed image; and performing spatial domain transformation on the portion of the first compressed image corresponding to the carrier frequency image to obtain the hidden image. Compared with existing technologies, this method can effectively resist steganalysis and has high security.

The application discloses an image hiding method and device based on compressed sensing and run-length coding. The method first compresses the size of a secret image needing security protection by using compressed sensing technology, then converts the decimal pixel value of the size-compressed secret image into a binary sequence, then compresses the binary sequence by using run-length coding to obtain a numerical sequence with a shorter length, and converts a cover image in a spatial domain into a frequency domain by using integer wavelet transform to obtain four subbands. The numerical sequence compressed twice has a similar form with the high-frequency subband coefficients of the cover image, and can directly replace the high-frequency subband coefficients to complete embedding operation. The application ingeniously combines compressed sensing, run-length coding and high-frequency subband embedding technology, greatly improves the quality of the camouflage image under the premise of ensuring high hiding capacity, and has the advantages of high capacity, low complexity and the like.

This invention provides an image hiding method based on a restricted Boltzmann machine and parallel compressed sensing. The method comprises two stages: encryption and embedding. In the encryption stage, the plaintext image is sequentially subjected to sparse decomposition, image scrambling, and thresholding. Then, a measurement matrix is ​​constructed using a random sequence for parallel compressed sensing. The image is then quantized, followed by further rotation scrambling and random diffusion to obtain the ciphertext image. In the embedding stage, the ciphertext image information is embedded into different wavelet coefficients of the carrier image using wavelet transform, and the embedding depth is dynamically selected based on the random sequence to improve the concealment and security of the embedded information. This invention effectively improves the randomness of the sequence while significantly increasing image processing efficiency, and achieves high-quality image reconstruction at a relatively low compression ratio. Furthermore, the encrypted image generated by this invention exhibits higher resistance to attacks and greater robustness.