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Camouflage assessment: Machine and human

Volonakis, Timothy N.; Matthews, Olivia E.; Liggins, Eric; Baddeley, Roland J.; Scott-Samuel, Nicholas E.; Cuthill, Innes C.


Tim Volonakis
Research Associate in Computer Vision

Olivia E. Matthews

Eric Liggins

Roland J. Baddeley

Nicholas E. Scott-Samuel

Innes C. Cuthill


© 2018 Elsevier B.V. A vision model is designed using low-level vision principles so that it can perform as a human observer model for camouflage assessment. In a camouflaged-object assessment task, using military patterns in an outdoor environment, human performance at detection and recognition is compared with the human observer model. This involved field data acquisition and subsequent image calibration, a human experiment, and the design of the vision model. Human and machine performance, at recognition and detection, of military patterns in two environments was found to correlate highly. Our model offers an inexpensive, automated, and objective method for the assessment of camouflage where it is impractical, or too expensive, to use human observers to evaluate the conspicuity of a large number of candidate patterns. Furthermore, the method should generalize to the assessment of visual conspicuity in non-military contexts.


Volonakis, T. N., Matthews, O. E., Liggins, E., Baddeley, R. J., Scott-Samuel, N. E., & Cuthill, I. C. (2018). Camouflage assessment: Machine and human. Computers in Industry, 99, 173-182.

Journal Article Type Article
Acceptance Date Mar 5, 2018
Publication Date Aug 1, 2018
Deposit Date Apr 4, 2018
Publicly Available Date Nov 2, 2019
Journal Computers in Industry
Print ISSN 0166-3615
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 99
Pages 173-182
Keywords camouflage assessment, observer modelling, visual search
Public URL
Publisher URL
Additional Information Additional Information : This is the author's accepted manuscript. The final published version is available here:


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