Salem Hussin, Saleh Hussin (2005) Improved Watermarking Algorithm Based on Discrete Wavelet Transform and Fibonacci Permutation. Masters thesis, Universiti Putra Malaysia.
Digital image watermark is an imperceptible, robust, secure message embedded into the image, which identify one or more owner, distributor, or recipient of the image, origin or status of the data or transaction dates. Watermarking is also used for data hiding, content labeling, broadcast monitoring, and integrity control applications. Digital watermarking resembles communication systems. Watermark is the sent message. Image is the watermark channel or carrier. Image pixels and possible attacks on marked image constitute the noise. Only the authorized parties' extracts the watermark message from the marked image by using detector. Digital watermarking has three major requirements. Watermark should be robust against noise and attacks, imperceptible and has the required capacity. These three requirements conflict with each other. To illustrate, increasing the watermark strength makes the system more robust but unfortunately decreases the perceptual quality. As a second example, increasing the capacity of the watermark decreases the robustness. In this thesis, the goal was to study digital image watermarking and develop watermarking algorithm that can achieve high imperceptibility, maximum capacity, and high robustness against image manipulation at the same time. This algorithm is based on the combination of Fibonacci permutation and discrete wavelet transforms (DWT). A binary image is used as the watermark and inserted into a mid-frequency wavelet subband of the permuted image. The watermarked image is reproduced by taking the inverse DWT and the inverse permutation. In extraction process the watermark is extracted from the watermarked image directly without using the original image. The experimental results have shown that the proposed watermark is invisible to human eyes and very robust against image manipulation, such as JPEG compression, median filtering, wiener filtering, and noises.
|Item Type:||Thesis (Masters)|
|Chairman Supervisor:||Elsadig Mohamed Ahmed Babiker, PhD|
|Call Number:||FK 2005 7|
|Faculty or Institute:||Faculty of Engineering|
|Deposited By:||Nur Izyan Mohd Zaki|
|Deposited On:||06 May 2010 08:03|
|Last Modified:||27 May 2013 07:26|
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