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Babak Mahdian
Researcher at Academy of Sciences of the Czech Republic
Publications - 29
Citations - 1602
Babak Mahdian is an academic researcher from Academy of Sciences of the Czech Republic. The author has contributed to research in topics: Digital image & JPEG. The author has an hindex of 12, co-authored 29 publications receiving 1399 citations. Previous affiliations of Babak Mahdian include Czech Technical University in Prague.
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Journal ArticleDOI
Detection of copy–move forgery using a method based on blur moment invariants
Babak Mahdian,Stanislav Saic +1 more
TL;DR: This work proposes a method to automatically detect and localize duplicated regions in digital images based on blur moment invariants, which allows successful detection of copy-move forgery, even when blur degradation, additional noise, or arbitrary contrast changes are present in the duplicates regions.
Journal ArticleDOI
Blind Authentication Using Periodic Properties of Interpolation
Babak Mahdian,Stanislav Saic +1 more
TL;DR: It is shown that interpolated signals and their derivatives contain specific detectable periodic properties, and a blind, efficient, and automatic method capable of finding traces of resampling and interpolation is proposed.
Journal ArticleDOI
Using noise inconsistencies for blind image forensics
Babak Mahdian,Stanislav Saic +1 more
TL;DR: This paper proposes a novel method capable of dividing an investigated image into various partitions with homogenous noise levels and introduces a segmentation method detecting changes in noise level using the additive white Gaussian noise.
Journal ArticleDOI
A bibliography on blind methods for identifying image forgery
Babak Mahdian,Stanislav Saic +1 more
TL;DR: An extensive list of blind methods for detecting image forgery is presented and an attempt has been made to make this paper complete by listing most of the existing references and by providing a detailed classification group.
Proceedings ArticleDOI
Detecting double compressed JPEG images
Babak Mahdian,Stanislav Saic +1 more
TL;DR: This paper focuses on image specific artifacts and proposes an automatic method capable of detecting them and is presented as a viable alternative to conventional photo-editing software.