基于图像Bag-of-Words模型的无载体信息隐藏

doi:10.3969/j.issn.0255-8297.2016.05.005

Abstract

Abstract:

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.

Key words: coverless information hiding, visual word, bag of words (BOW) model, image search

CLC Number:

TN911.73

ZHOU Zhi-li, CAO Yi, SUN Xing-ming. Coverless Information Hiding Based on Bag-of-Words Model of Image[J]. Journal of Applied Sciences, 2016, 34(5): 527-536.

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

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