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. Orthogonal Data Embedding for Binary Images in Morphological Transform Domain-A High-Capacity App
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
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.