Download PDFOpen PDF in browser

An improved image steganography model based on Deep Convolutional Neural Networks

EasyChair Preprint no. 7705

10 pagesDate: April 2, 2022

Abstract

In this paper, we propose an image steganography model with the use of a DeepCNN grounded autoencoder which allows extracting spatiotemporal features from images. It tends to hide four images in one other image taking into consideration equivalency in terms of size. Thus we try to encode and decode multiple secret images within a single, high-resolution cover image. The quantitative result of this model was arranged using the quantitative index "error per pixel", and the qualitative result was evaluated against the existing approaches.

Keyphrases: Auto-encoder, Deep CNN, image, spatio-temporal, Steganography

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:7705,
  author = {Mounir Telli and Mohamed Othmani and Hela Ltifi},
  title = {An improved image steganography model based on Deep Convolutional Neural Networks},
  howpublished = {EasyChair Preprint no. 7705},

  year = {EasyChair, 2022}}
Download PDFOpen PDF in browser