Image steganography method based on SE-ResNet

An image and secret image technology, applied in the field of image processing, can solve the problems of complex embedding and extraction process, and achieve the effects of enhanced invisibility, increased steganographic capacity, and optimized weights

Pending Publication Date: 2022-03-11
XIAN UNIV OF TECH
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Compared with the space domain steganography algorithm, the transformation domain steganography algorithm has more complex embedding and extraction processes

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Image steganography method based on SE-ResNet
  • Image steganography method based on SE-ResNet
  • Image steganography method based on SE-ResNet

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0040] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0041] The present invention is based on the SE-ResNet steganography method, such as figure 1 As shown, I cover Indicates the color carrier image, Icover-B Represents the B channel of the color carrier image, I cover-R and I cover-G Represent the R channel and G channel of the carrier image, I stego-B represents the B channel of the steganographic image, I stego Represents a steganographic image. The specific process is: the secret image M emb Input the Guest network branch of the encoding network. The Guest network branch is composed of 7 convolutional layers, each of which is composed of a conv convolution operation and a ReLU activation function. Conv convolution operation feature extraction, ReLu activation operation for nonlinear mapping. At the same time, the B channel I of the carrier image cover-B Input the Host network branch...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an image steganography method based on SE-ResNet. The image steganography method based on SE-ResNet specifically comprises the following steps: step 1, obtaining a B channel Icover-B of a secret image Memb and a carrier image Icover; step 2, respectively inputting a B channel Icover-B of the secret image Memb and the carrier image Icover obtained in the step 1 into a coding network, and obtaining a cascaded feature map; step 3, enabling the cascade feature map obtained in the step 2 to pass through three SE-ResNet blocks and two convolution layers to obtain a B channel Istego-B of a final steganographic image; step 4, acquiring a steganographic image Istego according to a result obtained in the step 3; and step 5, extracting to obtain a secret image Mext. By the adoption of the method, the image steganography capacity is improved, the invisibility of the image is enhanced, and secret information is not prone to being detected.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to an image steganography method based on SE-ResNet. Background technique [0002] Steganography is to hide secret information in multimedia data to achieve the purpose of concealing communication. The advantage is that ordinary people do not know the occurrence of secret communication, thus achieving higher security. From the point of view of the embedding position of secret information, traditional steganography algorithms can be divided into two categories: spatial domain steganography algorithms and transform domain steganography algorithms. The simplest and most representative spatial steganography algorithm is the least significant bit (LSB) algorithm, which first preprocesses the secret information into a binary number, and then combines the binary secret information with the least significant bit of each pixel in the carrier image Replacement, so as to achieve the pu...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06T1/00G06T9/00G06N3/04G06N3/08
CPCG06T1/0021G06T9/002G06N3/08G06N3/048G06N3/045
Inventor 刘晶杨慧
Owner XIAN UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap