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21 April 2020 Cover image selection for embedding based on different criteria
Rasber Dhahir Rashid
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Proceedings Volume 11399, Mobile Multimedia/Image Processing, Security, and Applications 2020; 113990V (2020) https://doi.org/10.1117/12.2560720
Event: SPIE Defense + Commercial Sensing, 2020, Online Only
Abstract
The main goal of image steganography techniques is to maximize embedding rate while minimizing the change of the cover image after embedding. Much work has been done on how sender would embed the secret message in the cover image (i.e. embedding techniques) but there is a few works focus on how the senders choose the cover images. One advantage of image steganography is that the cover image only acts as a carrier for the message and the embedder (sender) has the freedom to choose a cover image amongst a set of cover images those results in the least detectable stego image. The way of choosing the cover image is important and since it is available to the sender both the cover and stego images, then the senders are able to measure the embedding artifacts directly. Thus, we are interested in measures which are able to quantify such artifacts. We can use the cover-stego based on measures which we have employed in our work to select best cover image among set of images. The measures used are (1) Number of Modifications to the cover image could be thought as the most intuitive. The smaller the number of changes made the less detectable the resulting stego image should be, (2) Peak Signal to Noise Ratio (PSNR) which is obtained from the cover-stego image pairs where higher PSNR values are assumed to be indicative of lesser delectability, or (3) Based on the robustness to the steganalysis techniques. For the experiments we used a dataset of gray scale images with size of 512×512 resolutions as a cover image with different secret message size from 0.2 to 1.0 bits per pixel.
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Rasber Dhahir Rashid "Cover image selection for embedding based on different criteria", Proc. SPIE 11399, Mobile Multimedia/Image Processing, Security, and Applications 2020, 113990V (21 April 2020); https://doi.org/10.1117/12.2560720
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KEYWORDS
Steganography
Steganalysis
Image processing
Image quality
Information security
Image transmission
Computer security
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