作者投稿和查稿 主编审稿 专家审稿 编委审稿 远程编辑

计算机工程 ›› 2010, Vol. 36 ›› Issue (5): 154-155,. doi: 10.3969/j.issn.1000-3428.2010.05.056

• 安全技术 • 上一篇    下一篇

基于小波对比度和神经网络的图像隐写方法

张佳佳,盘宏斌,黄辉先   

  1. (湘潭大学信息工程学院,湘潭 411105)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2010-03-05 发布日期:2010-03-05

Image Steganographic Method Based on Wavelet Contrast and Neural Networks

ZHANG Jia-jia, PAN Hong-bin, HUANG Hui-xian   

  1. (College of Information Engineering, Xiangtan University, Xiangtan 411105)
  • Received:1900-01-01 Revised:1900-01-01 Online:2010-03-05 Published:2010-03-05

摘要: 为使通信安全在传输过程中提供较大的秘密信息嵌入量,并保持较好的载密图像质量,提出一种基于自组织特征映射神经网络和小波对比度的图像隐写方法。将载体图像分成固定大小的小块,采用小波一级分解并计算其小波对比度,利用自组织特征映射神经网络将小块分为3类,采用模算子技术嵌入秘密信息。实验结果表明,该方法有较大的嵌入量并保持良好的载密图像质量。

关键词: 隐写方法, 自组织特征映射神经网络, 小波对比度

Abstract: To provide larger capacity of the hidden secret data and to maintain a better visual quality of stego-image, this paper presents a image steganographic method based on Self-Organizing feature Map(SOM) neural networks and wavelet contrast. It divides an image into blocks, and decomposes every block into one-level wavelet to obtain the wavelet contrast. The method classifies blocks into 3 kindsby SOM, and embeds secret information with steganography, which is based on modulus. Experimental results show that the proposed method hides much more information and maintains a better visual quality of stego-image.

Key words: steganographic method, Self-Organizing feature Map(SOM) neural networks, wavelet contrast

中图分类号: