video compression with data hiding

7/29/2019 Video Compression With Data Hiding

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Video Compression with Data hiding & Data

Extraction

INTRODUCTION:Data hiding has been used in various applications like copyright protection,

authentication, fingerprinting, error concealment, broadcast monitoring, covert communication,

etc.Each application imposes different types of constraints in terms of capacity, security and

robustness.

Generally, there are two popular data embedding and extracting approaches spread

spectrum and quantization index modulation (QIM). We use a QIM based approach, where

quantization point is chosen based on parity of a hidden bit.

This is chosen because it can handle more information compared to spread spectrum techniques.

Even with compression, the size of the privacy information in our application usually exceeds

3000 bits per a 352 288 frame. Obviously, the perceptual quality after embedding such a large

payload is of great concern.

We proposed to hide large volume of information into the nonzero DCT terms after

quantization. This method cannot provide sufficient embedding capacity for our application

because surveillance videos have high temporal redundancy, so more than 80% of the DCT

coefficients will be zero in the inter-coded frames. The proposed system is to implement the

embedding in both zero and non-zero DCT coefficients but only in macro blocks with low inter

frame velocity. This framework deals only with minimizing perceptual distortion without

considering the increase in bit rate. Our algorithm considers both rate and distortion and

produces an optimal distribution of hidden bits among various DCT blocks. Our earlier work , a

heuristic method to reach a compromise in distortion and output rate but no formal optimization

is performed. Rate-distortion optimization is used for data hiding in MPEG audio. Their scheme

maximizes the channel capacity used for data hiding with a given distortion constraint.

Abstract:

This paper deals with data hiding in compressed video. Unlike data hiding in images

and raw video which operates on the images themselves in the spatial or transformed domain

which are vulnerable to steganalysis, we target the motion vectors used to encode and reconstruct


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both the forward predictive (P)-frame and bidirectional (B)-frames in compressed video. The

choice of candidate subset of these motion vectors are based on their associated macro block

prediction error, which is different from the approaches based on the motion vector attributes

such as the magnitude and phase angle, etc. A greedy adaptive threshold is searched for every

frame to achieve robustness while maintaining a low prediction error level. The secret message

bit stream is embedded in the least significant bit of both components of the candidate motion

vectors. The method is implemented and tested for hiding data in natural sequences of multiple

groups of pictures and the results are evaluated. The evaluation is based on two criteria:

minimum distortion to the reconstructed video and minimum overhead on the compressed video

size. Based on the aforementioned criteria, the proposed method is found to perform well and is

compared to a motion vector attribute-based method from the literature.


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Hardware & software requirements:

Hardware requirements

Processor : Pentium IV

Speed : Above 500 MHz

RAM capacity : 2 GB

Hard disk drive : 80 GB

Key Board : Samsung 108 keys

Mouse : Logitech Optical Mouse

Printer : DeskJet HP

Motherboard : Intel

Cabinet : ATX

Monitor : 17 Samsung

Software configuration

Operating System : Windows XP and above

Front end used : Java.

Back End : MS SQL .


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Existing System:

Data hiding has been used in various applications like copyright protection,

authentication, fingerprinting, error concealment, broadcast monitoring, covert communication,

etc. Each application imposes different types of constraints in terms of capacity, security and

robustness.

The drawback of these techniques is that it cannot be used with any other video

modification techniques besides scrambling. Using data hiding for privacy data preservation is

more flexible as it completely isolates preservation from modification. It can handle advanced

modification techniques such as object removal using video in painting.

Is imperative to design a data hiding scheme that is compatible with the compression

algorithm and at the same time, maximum perceptual distortion and the high output bit rate.

Proposed System:

Data hiding for privacy information preservation. Privacy is protected by obfuscating

images of individuals from the video and the original data is preserved by hiding it in the

compressed bit stream of the modified video. This is particularly useful when a condition arises

to prove the authenticity of the modified video.

To hide large volume of information into the nonzero DCT (Discrete Cosine Transform)

terms after quantization. This method cannot provide sufficient embedding capacity for our

application because surveillance videos have high temporal redundancy, so more than 80% of the

DCT coefficients will be zero in the inter-coded frames.

Implement the embedding in both zero and non-zero DCT coefficients but only in macro

blocks with low inter frame velocity. This framework deals only with minimizing perceptual

distortion without considering the increase in bit rate. Our algorithm considers both rate and

distortion and produces an optimal distribution of hidden bits among various DCT blocks.

The noise introduced by the hidden data causes a decline in efficiency of the motioncompensation process. As a result, the strategy proposed to choosing fixed locations for data

hiding in all frames significantly reduces the compression performance. The solution is to follow

an embedding strategy that can simultaneously minimize the distortion and the output bit rate.


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Modules:

1. Data Preprocessing of the dataset containing the Videos2. Designing and Implementing the Video Compression algorithm technique.3. Developing of Data hiding Algorithm and compacting with Video Compression technique.4. Extraction of Video using discrete cosine transform coefficient.

video compression with data hiding

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