Welcome to the InfoSci Platform
Using Statistical Texture Analysis for Medical Image Tamper Proofing

Using Statistical Texture Analysis for Medical Image Tamper Proofing

Samia Boucherkha, Mohamed Benmohamed
Copyright: © 2008 |Volume: 2 |Issue: 3 |Pages: 10
ISSN: 1930-1650|EISSN: 1930-1669|ISSN: 1930-1650|EISBN13: 9781615203253|EISSN: 1930-1669|DOI: 10.4018/jisp.2008070102
Cite Article Cite Article

MLA

Boucherkha, Samia, and Mohamed Benmohamed. "Using Statistical Texture Analysis for Medical Image Tamper Proofing." IJISP vol.2, no.3 2008: pp.18-27. http://doi.org/10.4018/jisp.2008070102

APA

Boucherkha, S. & Benmohamed, M. (2008). Using Statistical Texture Analysis for Medical Image Tamper Proofing. International Journal of Information Security and Privacy (IJISP), 2(3), 18-27. http://doi.org/10.4018/jisp.2008070102

Chicago

Boucherkha, Samia, and Mohamed Benmohamed. "Using Statistical Texture Analysis for Medical Image Tamper Proofing," International Journal of Information Security and Privacy (IJISP) 2, no.3: 18-27. http://doi.org/10.4018/jisp.2008070102

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

This article discusses an approach for both authentication of medical images and confidentiality for the related textual data in an online medical application paradigm. The image authentication is achieved in a soft manner through a feature-based digital signature while the confidentiality of the related patient information is achieved through reversible data hiding. The selected features are robust towards geometric transformations, while fragile towards texture alterations that are characteristic of medical images. The processing scheme is done in a block by block basis to permit the localization of tampered image’s regions. The effectiveness of the scheme, proven through experiments on a sample of medical images, enables us to argue that implementing mechanisms lying on this approach will help to maintain personal patient privacy and medical image integrity.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.