DocumentCode
1844334
Title
Robust Zero-Watermarking Algorithm Based on Invariant Centroid
Author
Liu Peili ; Tan Yuehui
Author_Institution
Dept. of Inf. Eng., Mech. Eng. Coll., Shijiazhuang, China
fYear
2013
fDate
21-23 June 2013
Firstpage
758
Lastpage
761
Abstract
In order to effectively resist geometric attacks and protect the security of information and copyrights of digital products, a digital image zerowatermarking algorithm based on geometric correction is proposed. According to the stability of the invariant centroid, we select the invariant centroid as a stable geometric reference point. The algorithm finds out the specific SIFT point which is the farthest to the reference point in image, then calculates geometric transformation parameters by changes of these two points´ positions. To hide information in image, we divide the image into blocks and apply QR decomposition in each block. After this, we extract the 2-Norm of the first row vector of matrix R in each block to form a sequence, and then transform it into a matrix after binary quantization. Finally, we make the XOR operation between the watermark and the matrix, and the result of the operation is the zero-watermarking. Experimental results show that the algorithm can effectively resist geometric attacks, with a high degree of correction accuracy and a strong robustness. By using the zero-watermarking method, the algorithm can also avoid the contradiction between invisibility and robustness.
Keywords
computational geometry; copyright; image watermarking; matrix algebra; quantisation (signal); transforms; 2-norm extraction; QR decomposition; SIFT point; XOR operation; binary quantization; digital product copyright protection; geometric attack resistance; geometric correction; geometric transformation parameters; image blocks; image division; information hiding; information security protection; invariant centroid stability; matrix row vector; point positions; robust digital image zero-watermarking algorithm; scale invariant feature transform; stable geometric reference point; Accuracy; Filtering algorithms; Matrix decomposition; Numerical stability; Robustness; Vectors; Watermarking; QR decomposition; invariant centroid; scale invariant feature transform(SIFT); zero-watermarking;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on
Conference_Location
Shiyang
Type
conf
DOI
10.1109/ICCIS.2013.204
Filename
6643120
Link To Document