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Tamper Localization and Self-Recovery Scheme for Medical Image Analysis Using SVD-based Fragile Watermarking

Yang, P, Shehab, A, Elhoseny, M, Muhammad, K, Sangaiah, A, Huang, H and Hou, G Tamper Localization and Self-Recovery Scheme for Medical Image Analysis Using SVD-based Fragile Watermarking. IEEE Access. ISSN 2169-3536 (Accepted)

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Abstract

Over the past decade advances in computer-based communication and health services, the need for image security becomes urgent to address the requirements of both safety and non-safety in medical applications. This paper proposes a new fragile watermarking based scheme for image authentication and self-recovery for medical applications. The proposed scheme locates image tampering as well as recovers the original image. A host image is broken into 4×4 blocks and Singular Value Decomposition (SVD) is applied by inserting the traces of block wise SVD into the Least Significant Bit (LSB) of the image pixels to figure out the transformation in the original image. Two authentication bits namely block authentication and self-recovery bits were used to survive the vector quantization attack. The insertion of self-recovery bits is determined with Arnold transformation, which recovers the original image even after a high tampering rate. SVD-based watermarking information improves the image authentication and provides a way to detect different attacked area. The proposed scheme is tested against different types of attacks such are text removal attack, text insertion attack, and copy and paste attack.

Item Type: Article
Additional Information: c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Computer Science
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date Deposited: 16 Jan 2018 11:27
Last Modified: 16 Jan 2018 11:27
URI: http://researchonline.ljmu.ac.uk/id/eprint/7856

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