Abstract
The histogram watermark, which performs watermark embedding by slightly modifying the histogram of the original image, has been a hot research topic in information hiding technology due to the superiority of its pixel modification during the watermark embedding process, which is independent of the pixel position. This property makes the histogram-based watermark strong resistant to geometric attacks, such as cropping attack, crossed attack, rotation attack, etc. In this paper, we propose a large capacity histogram-based robust watermarking algorithm based on three consecutive bins for the first time. In our scheme, we divide the shape of three consecutive bins into eight cases. According to these cases, we embed Information Number 0, 1, 2, 3, 4, 5, 6, or 7, respectively. The embedded information capacity reaches one bit per bin (bpb), and the amount of embedded information is equal to 200% of the previous existing algorithms. Experimental results show that the new algorithm not only has a large capacity of embedding information, but also has strong robustness to geometric attacks, as well as common image processing operations.
Highlights
With the rapid growth of popular and low-cost access to image editing applications, some intentional or unintentional manipulations of digital media during transmission are becoming available [1,2]
We propose a large capacity histogram-based watermarking algorithm for three consecutive bins
The improvement that we propose for watermark embedding differs from those proposed by recent state-of-the-art publications
Summary
With the rapid growth of popular and low-cost access to image editing applications, some intentional or unintentional manipulations of digital media during transmission are becoming available [1,2]. Developed an invariant watermarking solution to geometric attacks by using the histogram and the mean In their method, the histogram shape was used to embed the watermark based on the property that the histogram shape is only related to the pixel count of each grayscale, not the position of pixels. Zong et al [17] proposed a histogram-shape-related index method to form and select the most suitable pixel groups for embedding. With their method, some possible bad bins can be eliminated to some degree. A predefined threshold, together with a block-based pixel modification and new watermark embedding procedures, makes the proposed scheme a viable alternative to the histogram-based methods.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
