DocumentCode
1677884
Title
Geometric modeling of the wavelet coefficients for image watermarking
Author
Hamghalam, Mohammad ; Mirzakuchaki, Sattar ; Akhaee, Mohammad Ali
Author_Institution
Dept. of Electr. Eng., Iran Univ. of Sci. & Technol., Tehran, Iran
fYear
2013
Firstpage
27
Lastpage
32
Abstract
In this paper, a robust image watermarking method based on geometric modeling is presented. Eight samples of wavelet approximation coefficients on each image block are utilized to construct two line segments in the 2-D space. We change the angle formed between these line segments for data embedding. Geometrical tools are used to solve the tradeoff between the transparency and robustness of the watermark data. Due to embedding in the angle between two line segments, the proposed scheme has high robustness against the gain attacks. In addition, using the low frequency components of the image blocks for data embedding, high robustness against noise and compression attacks has been achieved. Experimental results confirm the validity of the theoretical analyses given in the paper and show the superiority of the proposed method against common attacks, such as Gaussian filtering, median filtering and scaling attacks.
Keywords
approximation theory; image watermarking; wavelet transforms; Gaussian filtering attacks; compression attacks; gain attacks; geometric modeling; image block; line segments; median filtering attacks; noise attacks; robust image watermarking method; scaling attacks; watermark data robustness; watermark data transparency; wavelet approximation coefficients; wavelet coefficients; Encoding; Filtering; Image segmentation; Optimized production technology; Quantization (signal); Robustness; Watermarking; geometric modeling; image watermarking; wavelet transform;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Vision and Image Processing (MVIP), 2013 8th Iranian Conference on
Conference_Location
Zanjan
ISSN
2166-6776
Print_ISBN
978-1-4673-6182-8
Type
conf
DOI
10.1109/IranianMVIP.2013.6779944
Filename
6779944
Link To Document