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A NOVEL JOINT DATA-HIDING AND COMPRESSION SCHEME
BASED ON SMVQ AND IMAGE INPAINTING
ABSTRACT
In this paper, we propose a novel joint data-hiding and compression scheme
for digital images using side match vector quantization (SMVQ) and image inpainting.
The two functions of data hiding and image compression can be integrated into one single
module seamlessly. Www.embeddedinnovationlab.com. On the sender side, except for
the blocks in the leftmost and topmost of the image, each of the other residual blocks in
raster-scanning order can be embedded with secret data and compressed simultaneously
by SMVQ or image inpainting adaptively according to the current embedding bit. “ Final
year eee projects in Bangalore” .Vector quantization is also utilized for some complex
blocks to control the visual distortion and error diffusion caused by the progressive
compression. After segmenting the image compressed codes into a series of sections by
the indicator bits, the receiver can achieve the extraction of secret bits and image
decompression successfully according to the index values in the segmented sections.
Experimental results demonstrate the effectiveness of the proposed scheme.
EXISTING SYSTEM
Final year vlsi projects in Bangalore In this scheme, rather than two
separate modules, only a single module is used to realize the two functions, i.e., image
compression and secret data embedding, simultaneously. The image compression in our
JDHC (Joint Data-Hiding and Compression) scheme is based mainly on the SMVQ
mechanism. According to the secret bits for embedding, the image compression based on
SMVQ is adjusted adaptively by incorporating the image inpainting technique. After
receiving the secret embedded and compressed codes of the image, one can extract the
embedded secret bits successfully during the image decompression.
DISADVANTAGES
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 Undesirable blocking artifacts affect the reconstructed videos or video frames.
 It gives low PSNR range
 Complexity is higher. final year engineering projects for eee in bangalore
PROPOSED SYSTEM
This paper proposes a high-capacity image-hiding scheme based on an adaptive
index. Data-hiding based on vector quantization (VQ) is a technique for hiding data in the
VQ index code. Final year engineering projects in Chennai.Data-hiding based on side
match vector quantization (SMVQ) has been proposed for improving the compression
rate of VQ-based data-hiding schemes. However, the hiding capacity of an SMVQ-based
data-hiding scheme is very low since, at most, only one secret bit is hidden in one index
code. To overcome this drawback and increase the capacity, the proposed method uses an
adaptive index to hide more bits in one index code. The weighted squared Euclidean
distance (WSED) can also be used to increase the probability of SMVQ to get greater
hiding capacity. http://www.embeddedinnovationlab.com
PROPOSED SYSTEM TECHNIQUE
 SMVQ (side match vector quantization)
ADVANTAGES
 In this technique gives better compression ratio
 It gives better psnr values
 Compared to existing, our technique is faster and computational complexity is
low. www.embeddedinnovationlab.com
 Bitstreams are generated with a multiple-resolution construction, the principal
content with higher resolution can be obtained when more bitstreams are received.
SOFTWARE REQUIREMENTS
 MATLAB 7.14 Version R2012
MATLAB

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The MATLAB high-performance language for technical computing integrates
computation, visualization, and programming in an easy-to-use environment where
problems and solutions are expressed in familiar mathematical notation.
 Data Exploration ,Acquisition ,Analyzing &Visualization
 Engineering drawing and Scientific graphics
 Analyzing of algorithmic designing and development
 Mathematical functions and Computational functions
 Simulating problems prototyping and modeling
 Application development programming using GUI building environment.
 Final year eee projects in Bangalore
Using MATLAB, you can solve technical computing problems faster than with
traditional programming languages, such as C, C++, and Fortran.

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Embedded Innovation Lab
Bangalore,Chennai
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