27-12-2011, 07:01 PM
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23-08-2012, 03:51 PM
This paper deals with data hiding in compressed video. Unlike data hiding in images and raw video which operates
06-03-2013, 11:43 AM
Data Hiding in Motion Vectors of Compressed Video Based on Their Associated Prediction Error
[attachment=52738]
Abstract
This paper deals with data hiding in compressed video.
Data hiding in images and raw video which operates on the images themselves in the spatial or transformed domain which are vulnerable to steganalysis.
The motion vectors used to encode and reconstruct both the forward predictive (P)-frame and bidirectional (B)-frames in compressed video.
A greedy adaptive threshold is searched for every frame to achieve robustness while maintaining a low prediction error level.
INTRODUCTION
DATA hiding [1] and watermarking in digital images and raw video have wide literature.
This paper targets the internal dynamics of video compression, specifically the motion estimation stage.
The data bits of the message are hidden in some of the motion vectors whose magnitude is above a predefined threshold, and are called candidate motion vectors (CMVs).
A single bit is hidden in the least significant bit of the larger component of each CMV.
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.
The embedding rate increases, more edge regions can be released adaptively for data hiding by adjusting just a few parameters.
[attachment=52738]
Abstract
This paper deals with data hiding in compressed video.
Data hiding in images and raw video which operates on the images themselves in the spatial or transformed domain which are vulnerable to steganalysis.
The motion vectors used to encode and reconstruct both the forward predictive (P)-frame and bidirectional (B)-frames in compressed video.
A greedy adaptive threshold is searched for every frame to achieve robustness while maintaining a low prediction error level.
INTRODUCTION
DATA hiding [1] and watermarking in digital images and raw video have wide literature.
This paper targets the internal dynamics of video compression, specifically the motion estimation stage.
The data bits of the message are hidden in some of the motion vectors whose magnitude is above a predefined threshold, and are called candidate motion vectors (CMVs).
A single bit is hidden in the least significant bit of the larger component of each CMV.
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.
The embedding rate increases, more edge regions can be released adaptively for data hiding by adjusting just a few parameters.