One of the main features of digital technology is that the digital media can be duplicated and reproduced easily. However, this allows unauthorized and illegal use of information, i.e. data piracy. To protect digital media against illegal attempts a signal, called watermark, is embedded into the multimedia data in a robust and invisible manner. A watermark is a short sequence of information, which contains owner&rsquo / s identity. It is used for evidence of ownership and copyright purposes.
In this thesis, we use fractional Fourier transformation (FrFT) domain, which combines space and spatial frequency domains, for watermark embedding and implement well-known secure spread spectrum watermarking approach. However, the spread spectrum watermarking scheme is fragile against geometrical attacks such as rotation and scaling. To gain robustness against geometrical attacks, an invisible template is inserted into the watermarked image in Fourier transformation domain. The template contains no information in itself but it is used to detect the transformations undergone by the image. Once the template is detected, these transformations are inverted and the watermark signal is decoded. Watermark embedding is performed by considering the masking characteristics of the Human Visual System, to ensure the watermark invisibility.
In addition, we implement watermarking algorithms, which use different transformation domains such as discrete cosine transformation domain, discrete Fourier transformation domain and discrete wavelet transformation domain for watermark embedding. The performance of these algorithms and the FrFT domain watermarking scheme is experimented against various attacks and distortions, and their robustness are compared.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12605837/index.pdf |
| Date | 01 February 2005 |
| Creators | Gokozan, Tolga |
| Contributors | Bozdagi Akar, Gozde |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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