The effect of contrast in camouflage patterns on detectability by human observers and CAMAELEON

Author
Heinrich, Daniela
Selj, Gorm Krogh
Date Issued
2015
Keywords
Kamuflasje
Måldeteksjon
Permalink
http://hdl.handle.net/20.500.12242/622
https://publications.ffi.no/123456789/622
DOI
10.1117/12.2176968
Collection
Articles
Description
Heinrich, Daniela; Selj, Gorm Krogh. The effect of contrast in camouflage patterns on detectability by human observers and CAMAELEON. Proceedings of SPIE, the International Society for Optical Engineering 2015 ;Volum 9476.
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Abstract
Evaluation of signature properties of military equipment is very important. It is crucial to apply the proper method out of many possible approaches, based on amongst others ranking by probability of detection, detection time, and distance to target, which have been carried out by various countries. In this paper we present results from camouflage pattern assessments utilising two different approaches, based on human observers (detection time) and simulations (CAMAELEON). CAMAELEON ranks camouflaged targets by their local contrast, orientation and spatial frequency, mimicking the human eye’s response, and is a rapid and low cost method for signature assessment. In our camouflage tests, human observers were asked to search for targets (in a natural setting) presented on a high resolution pc screen, and the corresponding detection times were recorded. In our study we find a good correspondence between the camouflage properties of the targets in most of our unique tests (scenes), but in some particular cases there is an interesting deviation. Two similar camouflage patterns (both were random samples of the pattern) were tested, and it seemed that the results depended on the way the pattern is attached to the test subject. More precisely, it may seem that high-contrast coloured patches of the pattern in the target outline were significantly different detected by humans compared to CAMAELEON. In this paper we discuss this deviation in the two signature evaluation methods and look at potential risks.
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