Blind Integrity Verification of Medical Images
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...
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Published in | IEEE transactions on information technology in biomedicine Vol. 16; no. 6; pp. 1122 - 1126 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
United States
IEEE
01.11.2012
Institute of Electrical and Electronics Engineers |
Subjects | |
Online Access | Get full text |
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Summary: | 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. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1089-7771 1558-0032 |
DOI: | 10.1109/TITB.2012.2207435 |