Orthogonal Data Embedding for Binary Images in Morphological Transform Domain – A Hig
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Orthogonal Data Embedding for Binary Images in Morphological Transform Domain – A High – Capacity Approach
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07-09-2013, 04:29 PM
ORTHOGONAL DATA EMBEDDING FOR BINARY IMAGES IN MORPHOLOGICAL TRANSFORM DOMAIN
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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.
Watermarking and data-hiding techniques have found wide applications in ownership identification, copy protection, fingerprinting, content authentication and annotation. The design requirements for a data-hiding or watermarking system are different catering for different applications. Recently authentication of digital documents has aroused great interest due to the wide applications in handwritten signatures, digital books, business documents, personal documents, maps, and engineering drawings. On the other hand, editing an image becomes easier with the powerful image editing tools and digital cameras. Authentication to detect tampering and forgery is thus of primary concern. To ensure the authenticity and integrity of these digital documents has increased the confidence level from the user point of view. Most data-hiding techniques for binary images are based on spatial domains 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. We observe that the morphological binary wavelet transform can be used to track the transitions in binary images by utilizing the detail coefficients. One rather intuitive idea in employing the morphological binary wavelet transform for data hiding is to use the detail coefficients as a location map to determine the data-hiding locations.
However, this makes it difficult to achieve blind watermark extraction due to the fact that once a pixel is flipped, the horizontal, vertical and diagonal detail coefficients will change correspondingly. This problem will be discussed in more detail in Section II. 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 .