10-09-2014, 09:46 AM
Watermarkingis
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1 Abstract:
Protection of digital multimedia content has become an increasinglyimportant issue for content owners and service providers. Watermarkingis identified as a major means to achieve copyright protection.
This watermarking algorithm will be designed and implemented based on LSB to embed watermark text as well as image inside images using watermarking approach by considering the human visual system (HVS) characteristics. HVS characteristics are used in this scheme to develop arobust watermarking scheme with a better tradeoff between robustnessand imperceptibility.
The proposed scheme will be tested against mostly known threats and So that to have goodrobustness. Also it will give a high quality watermarked image. MATLAB Program will be used to perform the watermarking task
2 Introduction:
Watermarking is a technique used to hide data or identifying information within digital multimedia.Our discussion will focus primarily on the watermarking of digital images, though digital video, audio, and documents are also routinely watermarked. Digital watermarking is becoming popular, especially for adding undetectable identifying marks, such as author or copyright information. The digital watermarking process embeds a signal into the media without significantly degrading its visual quality. Digital watermarking is a process to embed some information called watermark into different kinds of media called Cover Work. Digital watermarking is used to hide the information inside a signal, which cannot be easily extracted by the third party. Its widely used application is copyright protection of digital information. It is different from the encryption in the sense that it allows the user to access, view and interpret the signal but protect the ownership of the content. Digital watermarking involves embedding a structure in a host signal to “mark” its ownership. Digital watermarks are inside the information so that ownership of the information cannot be claimed by third party. While some watermarks are visible, most watermarks are invisible.
The best known Watermarking method that works in the Spatial Domain is the Least Significant Bit (LSB), which replaces the least significant bits of pixels selected to hide the information. This method has several implementation versions that improve the algorithm in certain aspects. The least significant bit (LSB) technique is used to embed information in a cover image. The LSB technique is that inside of a cover image, pixels are changed by bits of the secret message. These changes annot be perceived by the human visibility system. However, a passive attacker can easily extract the changed bits, since it has performed very simple operation. For example, Figure 1 shows the 1-bit LSB. In Figure 1, LSB can store 1-bit in each pixel. If the cover image size is 256 x 256 pixel image, it can thus store a total amount of 65,536 bits or 8,192 bytes of embedded data.
LITERATURE REVIEW
In the last ten years, the usage of digital imaging has been increased rapidly. Digital images are now widely distributed on the Internet and via CDs. Digital imaging allows an unlimited number of copies of images to be easily distributed and/or forged. This presents problems if the copied images are copyrighted.
The protection and enforcement of intellectual property rights has become an important issue in the digital world. Many approaches are available for protecting digital data; traditional methods include encryption, authentication and time stamping. The most popular approach is watermarking. Many researchers have proposed watermarking approaches and they try to find the best algorithm that can produce watermarked image with minimum distortion and has maximum performance.
The Least significant bit was first used by Trikel et al. (1993). Ten, Lee et al. (2008) modified LSB to decrease the distortion and increase the robustness by embedding randomly. The proposed algorithm modified LSB to get the minimum distortion and increase the robustness by redundancy. In this research work, Least Significant Bit (LSB) technique will be modified to get better results based on the distortion of the watermarked image.
A maximum capacity of the watermark text to be embedded is determined. If the length of the watermark text is less than the maximum capacity, multiple copies of the watermarked image will be embedded into the cover image. If the watermark text is more than the maximum capacity of the first LSB, the watermarked image is embedded in the second LSB. We also proposed an improved LSB algorithm which will be compared to the traditional LSB (Kurah and McHughes, 2011) and Lee et al.'s algorithm (2012) and Yang et al.'s (2012) algorithm.
In a digital image, information can be inserted directly into every bit of image information or the more busy areas of an image can be calculated so as to hide such messages in less perceptible parts of an image. Tirkel et al., were one of the first used techniques for image watermarking. Two techniques were presented to hide data in the spatial domain of images by them. These methods were based on the pixel value’s Least Significant Bit (LSB) modifications. The algorithm proposed by Kurah and McHughes to embed in the LSB and it was known as image downgrading Zheng, D (2007).
An example of the less predictable or less perceptible is Least Significant Bit insertion. This section explains how this works for an 8-bit grayscale image and the possible effects of altering such an image. The principle of embedding is fairly simple and effective. If we use a grayscale bitmap image, which is 8- bit, we would need to read in the file and then add data to the least significant bits of each pixel, in every 8-bit pixel. In a grayscale image each pixel is represented by 1 byte consist of 8 bits. It can represent 256 gray colors between the black which is 0 to the white which is 255.
The principle of encoding uses the Least Significant Bit of each of these bytes, the bit on the far right side. If data is encoded to only the last two significant bits (which are the first and second LSB) of each color component it is most likely not going to be detectable; the human retina becomes the limiting factor in viewing pictures (Titty, T.,2011).
JUSTIFICATION OF THE DISSERTATION WORK
believe that protecting intellectualmaterial on the web is one of the major issues concerningthe proper use of the internet. Digital imagesare a very characteristic part of this material foundonline and our target is to make people feel free toupload their images without hesitating because of thefear of their work being unauthorized used.
Watermarking is the ideal solution for protectingyour property of the images and keeping them visibleto the public as well, so research towards imperceptiblesecure and robust image watermarking techniquesis vital. As mentioned, there are already variousmethods that can achieve that, but every singlemethod requires attention and that’s because we cannot discriminate a specific method as the best. Everycase has its ideal solution and the same idea appliesfor image watermarking.Concerning watermarking, a system should efficientlywatermark images that are about to be uploadedon the web, where users copy and use imagesall the time and sometimes make certain modificationsto them. We considered important to take intoaccount this fact and provide a method which useswatermarks, robust under these modifications. Sucha modification might be scaling or even rotation especiallyif the image is an indeterminate depiction.