Seminar Topics & Project Ideas On Computer Science Electronics Electrical Mechanical Engineering Civil MBA Medicine Nursing Science Physics Mathematics Chemistry ppt pdf doc presentation downloads and Abstract

Full Version: Data Hiding in Motion Vectors of Compressed Video Based on Their Associated Predictio
You're currently viewing a stripped down version of our content. View the full version with proper formatting.
Data Hiding in Motion Vectors of Compressed Video Based on Their Associated Prediction Error



[attachment=27748]

Existing System:

DATA hiding and watermarking in digital images and raw video have wide literature. In case the data is extracted, it will be encrypted. But still there is a chance that the intruder can break the code.
However, we find that in most existing approaches, the choice of embedding positions within a cover image mainly depends on a pseudorandom number generator without considering the relationship between the image content itself and the size of the secret message.

Proposed System:
We expand the LSB matching revisited image steganography and propose an edge adaptive scheme which can select the embedding regions according to the size of secret message and the difference between two consecutive pixels in the cover image.
For lower embedding rates, only sharper edge regions are used while keeping the other smoother regions as they are. When the embedding rate increases, more edge regions can be released adaptively for data hiding by adjusting just a few parameters.
Advantages:
The proposed method is found to have lower distortion to the quality of the video and lower data size increase.

Modules:

1. Image Steganography
Analysis the image
JPEG Frame
MPEG Frame
Data hiding through image
2. Video Compression
3. Motion Vector of Video

Image Steganography:

We have chosen this stage because its contents are processed internally during the image encoding/ decoding which makes it hard to be detected by image steganalysis methods and is lossless coded, thus it is not prone to quantization distortions. In the literature, most work applied on data hiding in motion vectors relies on changing the motion vectors based on their attributes such as their magnitude, phase angle, etc. The data bits of the message are hidden in some of the image whose magnitude is above a predefined threshold. A single bit is hidden in the least significant bit of the larger component of each image.


Analysis the image:

Admin choose the image and has to be entered the text, image or shape, the admin has the permission to alter the image as he like; this is the first process of analyzing.


JPEG Frame:

At the encoder, the intrapredicted (I)-frame is encoded using regular image techniques similar to JPEG but with different quantization table and step; hence the decoder can reconstruct it independently. The Algorithm tests the robustness of the hidden message to the quantization effect of the JPEG Compression. Using the variable macro block sizes is 8*8 pixel analysis of the image.


MPEG Frame:
In the commonly used Motion Picture Expert Group (MPEG) standard, it is ordered into groups of pictures (GOPs). The temporal redundancy between frames is exploited using block-based motion estimation that is applied on macro blocks of size is 16*16 Pixel Analysis in or and searched in target frame(s).