By Topic

Blind Integrity Verification of Medical Images

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Hui Huang ; Inst. Mines-Telecom, Telecom Bretagne, Brest, France ; Coatrieux, G. ; Huazhong Shu ; Limin Luo
more authors

This paper presents the first method of digital blind forensics within the medical imaging field with the objective to detect whether an image has been modified by some processing (e.g., filtering, lossy compression, and so on). It compares two image features: the histogram statistics of reorganized block-based discrete cosine transform coefficients, originally proposed for steganalysis purposes, and the histogram statistics of reorganized block-based Tchebichef moments. Both features serve as input of a set of support vector machine classifiers built in order to discriminate tampered images from original ones as well as to identify the nature of the global modification one image may have undergone. Performance evaluation, conducted in application to different medical image modalities, shows that these image features can help, independently or jointly, to blindly distinguish image processing or modifications with a detection rate greater than 70%. They also underline the complementarity of these features.

Published in:

Information Technology in Biomedicine, IEEE Transactions on  (Volume:16 ,  Issue: 6 )