Image Provenance Analysis

Daniel Moreira; William Theisen; Walter Scheirer; Aparna Bharati; Joel Brogan; Anderson Rocha

doi:10.1007/978-981-16-7621-5_15

Image Provenance Analysis

Daniel Moreira, William Theisen, Walter Scheirer, Aparna Bharati, Joel Brogan, Anderson Rocha

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

The literature of multimedia forensics is mainly dedicated to the analysis of single assets (such as sole image or video files), aiming at individually assessing their authenticity. Different from this, image provenance analysis is devoted to the joint examination of multiple assets, intending to ascertain their history of edits, by evaluating pairwise relationships. Each relationship, thus, expresses the probability of one asset giving rise to the other, through either global or local operations, such as data compression, resizing, color-space modifications, content blurring, and content splicing. The principled combination of these relationships unveils the provenance of the assets, also constituting an important forensic tool for authenticity verification. This chapter introduces the problem of provenance analysis, discussing its importance and delving into the state-of-the-art techniques to solve it.

Original language	American English
Title of host publication	Computer Science: Faculty Publications and Other Works
DOIs	https://doi.org/10.1007/978-981-16-7621-5_15
State	Published - Apr 2 2022

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10.1007/978-981-16-7621-5_15License: Unspecified

Image Provenance Analysis

http://ecommons.luc.edu/cs_facpubs/336

Cite this

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title = "Image Provenance Analysis",

abstract = "The literature of multimedia forensics is mainly dedicated to the analysis of single assets (such as sole image or video files), aiming at individually assessing their authenticity. Different from this, image provenance analysis is devoted to the joint examination of multiple assets, intending to ascertain their history of edits, by evaluating pairwise relationships. Each relationship, thus, expresses the probability of one asset giving rise to the other, through either global or local operations, such as data compression, resizing, color-space modifications, content blurring, and content splicing. The principled combination of these relationships unveils the provenance of the assets, also constituting an important forensic tool for authenticity verification. This chapter introduces the problem of provenance analysis, discussing its importance and delving into the state-of-the-art techniques to solve it.",

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AU - Theisen, William

AU - Scheirer, Walter

AU - Bharati, Aparna

AU - Brogan, Joel

AU - Rocha, Anderson

PY - 2022/4/2

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