Multimedia Data Hiding and Authentication via Halftoning and Coordinate Projection
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ultimedia Data Hiding and Authentication via Halftoning and Coordinate Projection Chai Wah Wu IBM Research Division, Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, NY 10598, USA Email: [email protected] Received 4 May 2001 and in revised form 14 September 2001 We present image data hiding and authentication schemes based on halftoning and coordinate projection. The proposed data hiding scheme can embed images of the same size and similar bit depth into the cover image and robustness against compression is demonstrated. The image authentication scheme is based on the data hiding scheme and can detect, localize, and repair the tampered area of the image. Furthermore, the self-repairing feature of the authentication scheme has a hologram-like quality; any portion of the image can be used to reconstruct the entire image, with a greater quality of reconstruction as the portion size increases. Keywords and phrases: data hiding, authentication, tamper detection, self-repairing images, error diffusion, digital halftoning, coordinate projection.
1. INTRODUCTION Recently, there has been much interest in multimedia data hiding, where information is imperceptibly embedded into multimedia content such as images and music [1]. The embedded data can contain ownership identification, tracking information, recipient information, time stamps, authentication data, and other information useful for various applications such as copyright protection, data integrity verification, verification of origin of data, recipient tracking, and so forth. In many applications, the main requirement is that the embedding changes the multimedia content imperceptibly. In this paper, we describe a system of embedding images into a source image by using digital halftoning algorithms and coordinate projections. In particular, we show how an entire image can be embedded into another source image and illustrate design requirements for robustness against distortions such as JPEG compression. The proposed embedding method can also be used in an image authentication scheme, where changes to an image can be detected, localized, and repaired. The repair operation reconstructs the original source image using information distributed over the entire image. In this sense it exhibits hologram-like properties; any portion of the image can be used to reconstruct the entire image. The larger the portion used for reconstruction, the higher the fidelity of the reconstructed image. 2.
DATA EMBEDDING AND EXTRACTION ALGORITHMS
We consider images represented as matrices of vectors. For example, an image M is represented as an n × m matrix of
d-dimensional vectors. The (i, j)th entry of M , denoted as M(i, j), is called the (i, j)th pixel of M . Each pixel M(i, j) is a d-dimensional vector, where d denotes the dimension of the color space, that is, d = 1 for a grayscale image, d = 3 for an image in RGB or LAB color space and d = 4 for an
image in CMYK space. We assume that each pixel is in the d-dimensional set S d . In many current image formats, S d = {
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