Can people identify original and manipulated photos of real-world scenes?

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Abstract

Advances in digital technology mean that the creation of visually compelling photographic fakes is growing at an incredible speed. The prevalence of manipulated photos in our everyday lives invites an important, yet largely unanswered, question: Can people detect photo forgeries? Previous research using simple computer-generated stimuli suggests people are poor at detecting geometrical inconsistencies within a scene. We do not know, however, whether such limitations also apply to real-world scenes that contain common properties that the human visual system is attuned to processing. In two experiments we asked people to detect and locate manipulations within images of real-world scenes. Subjects demonstrated a limited ability to detect original and manipulated images. Furthermore, across both experiments, even when subjects correctly detected manipulated images, they were often unable to locate the manipulation. People’s ability to detect manipulated images was positively correlated with the extent of disruption to the underlying structure of the pixels in the photo. We also explored whether manipulation type and individual differences were associated with people’s ability to identify manipulations. Taken together, our findings show, for the first time, that people have poor ability to identify whether a real-world image is original or has been manipulated. The results have implications for professionals working with digital images in legal, media, and other domains.

Item Type: Journal Article
Subjects: T Technology > TR Photography
Divisions: Faculty of Science, Engineering and Medicine > Science > Psychology
Library of Congress Subject Headings (LCSH): Image processing -- Digital techniques., Photography -- Retouching, Visual perception., Computer crimes -- Investigation., Forensic psychology., Photography -- Digital techniques
Journal or Publication Title: Cognitive Research : Principles and Implications
Publisher: Springer
ISSN: 2365-7464
Official Date: 18 July 2017
Dates:
Date
Event
18 July 2017
Published
12 June 2017
Accepted
Volume: 2
Article Number: 30
DOI: 10.1186/s41235-017-0067-2
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons open licence)
Date of first compliant deposit: 13 June 2017
Date of first compliant Open Access: 22 January 2018
RIOXX Funder/Project Grant:
Project/Grant ID
RIOXX Funder Name
Funder ID
UNSPECIFIED
Economic and Social Research Council
Related URLs:
URI: https://wrap.warwick.ac.uk/89106/

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