收稿日期: 2016-08-05
修回日期: 2016-08-18
网络出版日期: 2016-09-30
基金资助
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
Coverless Information Hiding Based on Bag-of-Words Model of Image
Received date: 2016-08-05
Revised date: 2016-08-18
Online published: 2016-09-30
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。
关键词： 无载体信息隐藏; bag of words模型; 视觉词汇; 图像搜索
周志立, 曹燚, 孙星明 . 基于图像Bag-of-Words模型的无载体信息隐藏[J]. 应用科学学报, 2016 , 34(5) : 527 -536 . DOI: 10.3969/j.issn.0255-8297.2016.05.005
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.
[1] 沈昌祥,张焕国,冯登国. 信息安全综述[J]. 中国科学,2007, 37(2): 129-150. Shen C X, Zhang H G, Feng D G. A survey of information security [J]. Science China, 2007, 37(2): 129-150. (in Chinese)
[2] Tirkel A Z, Rankin G A, Schyndel R V. Electronic watermark [C]//Digital Image Computing, Technology and Applications, 1993.
[3] Yang C H, Weng C Y, Wang S J. Adaptive data hiding in edge areas of images with spatial LSB domain systems [J]. IEEE Transactions on Information Forensics & Security, 2008, 3(3): 488-497.
[4] Bender W R, Gruhl D, Morimoto N. Techniques for data hiding [J]. IBM Systems Journal, 1996, 35(3.4): 313-336.
[5] Shi Y Q. Reversible data hiding [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2006, 16(3): 354-362.
[6] Ruanaidh J J K O, Dowling W J, Boland F M. Phase watermarking of digital images [C]// International Conference on Image Processing, 1996: 239-242.
[7] 许德合,朱长青,王奇胜. 利用DFT幅度和相位构建矢量空间数据水印模型[J]. 北京邮电大学学 报,2011, 34(5): 25-28.Xu D H, Zhu C Q, Wang Q S. A construction of digital watermarking model for the vector geospatial data based on magnitude and phase of DFT [J]. Journal of Beijing University of Posts and Telecommunications, 2011, 34(5): 25-28. (in Chinese)
[8] 司应硕,杨文涛,张森. 基于数字图像的信息隐藏技术研究[J]. 计算机光盘软件与应用,2011, 16: 160-161. Si Y S, Yang W T, Zhang S. Information hidingtechnology research based on digital image [J]. Computer CD Software and Application, 2011, 16: 160-161. (in Chinese)
[9] Cox I J, Kilian J, Leighton F T. Secure spread spectrum watermarking for multimedia [J]. IEEE Transactions on Image Processing, 2010, 6(12): 1673-87.
[10] Hsieh M S, Tseng D C, Huang Y H. Hiding digital watermarks using multiresolution wavelet transform [J]. IEEE Transactions on Industrial Electronics, 2001, 48(5): 875-882.
[11] Lin W H, Horng S J, Kao T W. An efficient watermarking method based on significant difference of wavelet coefficient quantization [J] . IEEE Transactions on Multimedia, 2008, 10(5): 746-757.
[12] Zhou Z, Sun H, Harit R. Coverless image steganography without embedding [C]// Cloud Computing and Security. Springer International Publishing, 2015: 123-132.
[13] Chen X, Sun H, Tobe Y. Coverless information hiding method based on the chinese mathematical expression [C]// Cloud Computing and Security. Springer International Publishing, 2015: 133-143.
[14] Yang J, Jiang Y G, Hauptmann A G. Evaluating bag-of-visual-words representations in scene classification [C]// International Workshop on Workshop on Multimedia Information Retrieval. ACM, 2007: 197-206.
[15] Hartigan J A, Wong M A. A K-means clustering algorithm [J]. Applied Statistics, 2013, 28(1): 100-108.
[16] Lowe D G. Distinctive image features from scale-invariant keypoints [J]. International Journal of Computer Vision, 2004, 60(2): 91-110.
[17] Jegou H, Douze M, Schmid C. Hamming embedding and weak geometric consistency for large scale image search [C]// European Conference on Computer Vision. Springer-Verlag, 2008: 1.1-1.1.
/
| 〈 |
|
〉 |
