Can people identify original and manipulated photos of real-world scenes?
Open accessAbstract
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.
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Past work in the cognitive science of media forensics has demonstrated that people are not good at perceiving and reasoning about shadow, reflection, and other physical implausibility cues.
“Past work in the cognitive science of media forensics has demonstrated that people are not good at perceiving and reasoning about shadow, reflection, and other physical implausibility cues (9–12).”
From Deepfake detection by human crowds, machines, and machine-informed crowds (2022) · cites this paper as [11]
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- Authors
- Nightingale, S. J., Wade, K. A., & Watson, D. G.
- Affiliations
- University of Warwick (GB)
- Corresponding author
- Nightingale, Sophie J.
- Venue
- Cognitive Research: Principles and Implications
- Published
- 2017-07-18
- Volume
- 2
- Issue
- 1
- Pages
- 30-30
- ISSN
- 2365-7464 (ISSN-L)
- PMC
- PMC5514174
- OpenAlex
- W2731865786
- Cited by
- 135
- References
- 57
- Citations by year
- 2026: 7 · 2025: 12 · 2024: 18 · 2023: 14 · 2022: 20 · 2021: 21 · 2020: 21 · 2019: 13 · 2018: 7 · 2017: 2
- FWCI
- 4.88
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Cognitive Research Principles and Implications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Warwick Research Archive Portal (University of Warwick) (acceptedVersion, cc-by-sa)
- Warwick Research Archive Portal (University of Warwick) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Lancaster EPrints (Lancaster University) (submittedVersion)
- Funders
- Economic and Social Research Council (1360334)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Aesthetic Perception and Analysis
- Keywords
- image tampering, real-world scenes, visual perception, pixel structure, individual differences, image forensics
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