Robust Digital Video Watermarking using Reversible Data Hiding and Visual Cryptography

Watermarking is a major image processing application used to authenticate user documents by embedding and hiding some authenticated piece of information behind an image, audio or the video file. For example, copyright symbols or signatures are often used. Our proposed work is to develop and implement an improved layered approach to video watermarking. The traditional watermarking approach tends to embed an entire watermark image within each video frame or within random video frames to give the appearance of a hidden watermark to the casual observer. This work proposes a more efficient and secure approach to perform watermarking, by using sub image classification. That is to say, selected frames only will contain a fractional number of pixels from the watermark image. We take k bits from the watermark and store then within a video frame, depending on the size of that watermark image. Our algorithm is capable of hiding high capacity information over video frames. The novel approach is to partially distribute the watermarking data over a set of frames until the entire watermark is eventually distributed throughout the entire video. The originality our technique is that it is a histogram inspired and reversible watermarking approach as defined with visual cryptography. Our approach hides similar watermarking pixels with frames of a similar appearance. Differing sets of watermark pixels are thus embedded within dissimilar frames, thus making the system more robust. It will provide a high degree of authentication, as the extraction of information from a single frame only will not reveal the entire watermarking data, or even give any obvious indication that it contains a fraction of the watermark pixels. The resilience of our technique will be tested by performing various systematic attacks upon a series of videos watermarked in this manner

Comparison of DCT, SVD and BFOA based multimodal biometric watermarking systems

AbstractDigital image watermarking is a major domain for hiding the biometric information, in which the watermark data are made to be concealed inside a host image imposing imperceptible change in the picture. Due to the advance in digital image watermarking, the majority of research aims to make a reliable improvement in robustness to prevent the attack. The reversible invisible watermarking scheme is used for fingerprint and iris multimodal biometric system. A novel approach is used for fusing different biometric modalities. Individual unique modalities of fingerprint and iris biometric are extracted and fused using different fusion techniques. The performance of different fusion techniques is evaluated and the Discrete Wavelet Transform fusion method is identified as the best. Then the best fused biometric template is watermarked into a cover image. The various watermarking techniques such as the Discrete Cosine Transform (DCT), Singular Value Decomposition (SVD) and Bacterial Foraging Optimization Algorithm (BFOA) are implemented to the fused biometric feature image. Performance of watermarking systems is compared using different metrics. It is found that the watermarked images are found robust over different attacks and they are able to reverse the biometric template for Bacterial Foraging Optimization Algorithm (BFOA) watermarking technique

Intensifying the Security of Multiomodal Biometric Authentication System using Watermarking

In Multimodal biometrics system two or more biometric attributes are combined which makes it far more secure than unimodal system as it nullifies all the vulnerabilities of it. But with the prompt ontogenesis of information technology, even the biometric data is not secure. There is one such technique that is implemented to secure the biometric data from inadvertent or deliberate attacks is known as Digital watermarking. This paper postulate an approach that is devise in both the directions of enlarging the security through watermarking technique and improving the efficiency of biometric identification system by going multimodal. Three biometric traits are consider in this paper two of them are physical traits i.e. ; face, fingerprint and one is behavioral trait (signature).The biometric traits are initially metamorphose using Discrete Wavelet and Discrete Cosine Transformation and then watermarked using Singular Value Decomposition. Scheme depiction and presented results rationalize the effectiveness of the scheme