基于图像Bag-of-Words模型的无载体信息隐藏  

Coverless Information Hiding Based on Bag-of-Words Model of Image

作　　者：周志立[1] 曹燚[1] 孙星明[1] 

机构地区：[1]南京信息工程大学计算机与软件学院,南京210044

出　　处：《应用科学学报》2016年第5期527-536,共10页Journal of Applied Sciences

基　　金：国家自然科学基金(No.61602253;No.U1536206;No.61232016;No.U1405254;No.61373133;No.61502242);江苏省自然科学基金(No.BK20150925);南京信息工程大学引进人才启动资金(No.2014r024);江苏高校优势学科建设工程PAPD基金;大气环境与装备技术协同创新中心(CICAEET)基金资助

摘　　要：介绍一种基于bag-of-words(BOW)模型的无载体信息隐藏方法.该方法使用BOW模型提取图像的视觉关键词(visual words,VW)以表达待隐藏的文本信息,从而实现文本信息在图像中的隐藏.首先使用BOW模型提取图像集中每幅图像的VW,构建文本信息的关键词和VW的映射关系库;然后把每幅图像分为若干子图像,统计每一幅子图像的VW频数直方图,选择频数最高的VW表示该子图像;最后根据构建的文本关键词和子图像VW的映射关系库,搜索出与待隐藏文本信息存在映射关系的子图像序列,将含有这些子图像的图像作为含密图像进行传递.实验结果和分析表明,该隐藏算法在抗隐写分析、鲁棒性和安全性方面均有良好的表现.This paper introduces a coverless information hiding method based on the bagof-words model（BOW）.To hide text information into an image,visual words are extracted to represent the text information.Visual words from an image set are extracted using a BOW model,and a mapping relation between keywords in the text information and visual words is established.Each image is then divided into several sub-images.For each sub-image,a histogram of visual words is computed,and visual words having the largest values in the histogram selected to represent the sub-image.According to the mapping relation,a set of sub-images with visual words related to the text information is found.The images containing these sub-images are used as stego-images for secret communication.The experimental results and analysis show that the proposed method has good performance in anti-steganalysis capability,robustness against common attacks,and security.

关 键 词：无载体信息隐藏 BAG of words模型 视觉词汇 图像搜索 

分 类 号：TN911.73[电子电信—通信与信息系统]