08-16-2017, 10:11 PM
Orthogonal Data Embedding for Binary Images in
Morphological Transform Domain-A High- Capacity Approach
ABSTRACT:
This paper proposes a data-hiding technique for binary images in morphological transform domain for authentication purpose. To achieve blind watermark extraction, it is difficult to use the detail coefficients directly as a location map to determine the data-hiding locations. Hence, we view flipping an edge pixel in binary images as shifting the edge location one pixel horizontally and vertically. Based on this observation, we propose an interlaced morphological binary wavelet transform to track the shifted edges, which thus facilitates blind watermark extraction and incorporation of cryptographic signature.
Unlike existing block-based approach, in which the block size is constrained by 3 *3 pixels or larger, we process an image in 2* 2 pixel blocks. This allows flexibility in tracking the edges and also achieves low computational complexity. The two processing cases that flipping the candidates of one does not affect the flip ability conditions of another are employed for orthogonal embedding, which renders more suitable candidates can be identified such that a larger capacity can be achieved. A novel effective Backward-Forward Minimization method is proposed, which considers both backwardly those neighboring processed embeddable candidates and forwardly those unprocessed flip able candidates that may be affected by flipping the current pixel.
EXISTING SYSTEM:
In Existing block-based approach, in which the block size is constrained by 3* 3 pixels or larger, we process an image in 2* 2 pixel blocks. This allows flexibility in tracking the edges and also achieves low computational complexity. The two processing cases that flipping the candidates of one does not affect the flippability conditions of another are employed for orthogonal embedding, which renders more suitable candidates can be identified such that a larger capacity can be achieved.
PROPOSED SYSTEM:
We Proposed present a high-capacity data-hiding scheme for binary images authentication based on the interlaced morphological binary wavelet transforms. The relationship between the coefficients obtained from different transforms is utilized to identify the suitable locations for watermark embedding such that blind watermark extraction can be achieved. Two processing cases that are not intersected with each other are employed for orthogonal embedding in such a way that not only can the capacity be significantly increased, but the visual distortion can also be minimized. Results of comparative experiments with other methods reinforce the present scheme s superiority in being able to attain larger capacity while maintaining acceptable visual distortion and low computational cost.
The goal of authentication is to ensure that a given set of data comes from a legitimate sender and the content integrity is preserved. Hard authentication rejects any modification made to a multimedia signal, whereas soft authentication differentiates legitimate processing from malicious tampering This paper focuses on hard authenticator watermark-based authentication.
Specifically, we investigate the problem of data hiding for binary images in morphological transform domain. Generally speaking, data hiding in real-valued transform domain does not work well for binary images due to the quantization errors introduced in the pre/post-processing In addition; embedding data using real-valued coefficients requires more memory space. The idea of designing an interlaced transform to identify the embeddable locations is motivated by the fact that some transition information is lost during the computation of a single transform and there is a need to keep track of transitions between two and three pixels for binary images data hiding. Specifically, we process the images based on 2*2 pixel blocks and combine two different processing cases that the flippability conditions of one are not affected by flipping the candidates of another for data embedding, namely orthogonal embedding
HARDWARE REQUIREMENTS
Hard disk : 40 GB
RAM : 512mb
Processor : Pentium IV
Monitor : 17 Color Monitor
SOFTWARE REQUIREMENTS
Front-End : VB.NET 2005
Coding Language : C#
Operating System : Windows XP.