Date of Award:

5-2010

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Computer Science

Committee Chair(s)

Xiaojun Qi

Committee

Xiaojun Qi

Committee

Steven W. Clyde

Committee

Vicki H. Allan

Abstract

This thesis presents a novel singular-value-based semi-fragile watermarking scheme for image content authentication with tampering localization. The proposed scheme first generates a secured watermark bit sequence by performing a logical "xor" operation on a content-based watermark and content-independent watermark, wherein the content-based watermark is generated by a singular-value-based watermark bit sequence that represents intrinsic algebraic image properties, and the content-independent watermark is generated by a private-key-based random watermark bit sequence. It next embeds the secure watermark in the approximation subband of each non-overlapping 4×4 block using the adaptive quantization method to generate the watermarked image. The image content authentication process starts with regenerating the secured watermark bit sequence following the same process mentioned in the secured watermark bit sequence generation. It then extracts a possibly embedded watermark using the parity of the quantization results from the probe image. Next, the authentication process constructs a binary error map, whose height and width are a quarter of those of the original image, using the absolute difference between the regenerated secured watermark and the extracted watermark. It finally computes two authentication measures (i.e., M1 and M2), with M1 measuring the overall similarity between the regenerated watermark and the extracted watermark, and M2 measuring the overall clustering level of the tampered error pixels. These two authentication measures are further seamlessly integrated in the authentication process to confirm the image content and localize any possible tampered areas. The extensive experimental results show that the proposed scheme outperforms four peer schemes and is capable of identifying intentional tampering, incidental modification, and localizing tampered regions.

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