Method and system for large-capacity image steganography and recovery based on invertible neural networks
AssigneeNankai University
InventorsShaoping Lu, Rong Wang, Tao Zhong
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Abstract
The present disclosure provides a method and system for large-capacity image steganography and recovery based on an invertible neural networks. The method is intended to embed one or more hidden images into a single host image, and recover all the hidden images from a stego image. The method designs an image steganography model that supports bidirectional mapping. The model includes cascaded invertible modules containing a host branch and a hidden branch. A hidden image is embedded into a host image through forward mapping to form a stego image, and the host image and the hidden image are separated and recovered from the single stego image through reverse mapping.
Claims14
A method for large-capacity image steganography and recovery based on an invertible neural networks, wherein an invertible neural networks model that supports bidirectional mapping is configured to complete tasks of embedding hidden images into a host image and recovering the hidden images from a stego image, and the invertible neural networks model comprises cascaded invertible modules containing a host branch and a hidden branch, the method comprising the following steps:
- a first part:
- embedding hidden images
- a. inputting the host image and the hidden image:
- importing one or more hidden images and a selected host image into a forward mapping input end of the invertible neural networks model as forward inputs;
- b. embedding image features:
- embedding feature information of the hidden image into the host image through the forward mapping of the invertible neural networks;
- and
- c. generating a stego image:
- taking forward output of a host branch of the invertible neural networks as the stego image, and specifying forward output of a hidden branch as a constant matrix containing no effective information;
- a second part:
- recovering the hidden images
- d. inputting the stego image:
- importing the stego image and the constant matrix obtained in step c into a reverse mapping input end of the invertible neural networks model as reverse inputs;
- e. separating the image features:
- separating features of the host image and the hidden image from the stego image through the reverse mapping of the invertible neural networks;
- and
- f. recovering the hidden image:
- taking reverse output of the host branch of the invertible neural networks as a recovered host image, and reverse output of the hidden branch as a recovered hidden image.
A method for large-capacity image steganography based on an invertible neural networks, wherein the method for large-capacity image steganography is implemented based on the invertible neural networks, the invertible neural networks comprises invertible modules, the invertible module comprises a host branch and a hidden branch, and the method for large-capacity image steganography comprises:
- inputting a host image and a hidden image;
- embedding feature information of the hidden image into the host image through forward mapping of the invertible neural networks;
- forwardly outputting a stego image by utilizing the host branch of the invertible neural networks, wherein the stego image is an image obtained by embedding the feature information of the hidden image into the host image;
- and
- forwardly outputting a constant matrix by utilizing the hidden branch of the invertible neural networks, wherein the constant matrix does not contain effective information of the hidden image.
A system for large-capacity image steganography based on an invertible neural networks, wherein the system for large-capacity image steganography is implemented based on the invertible neural networks, the invertible neural networks comprises invertible modules, and the invertible module comprises a host branch and a hidden branch, the system for large-capacity image steganography comprising:
- an input module, configured to input a host image and a hidden image;
- an information embedding module, configured to embed feature information of the hidden image into the host image through forward mapping of the invertible neural networks;
- a stego image output module, configured to forwardly output a stego image by utilizing the host branch of the invertible neural networks, wherein the stego image is an image obtained by embedding the feature information of the hidden image into the host image;
- and
- a constant matrix output module, configured to forwardly output a constant matrix by utilizing the hidden branch of the invertible neural networks, wherein the constant matrix does not contain effective information of the hidden image.
Dependencies are inferred from the claim text.