Disruptive coloration, crypsis and edge detection in early visual processing

Stevens, Martin; Cuthill, Innes C.

doi:10.1098/rspb.2006.3556

Cited by 219 publications

(211 citation statements)

References 34 publications

Supporting

Mentioning

207

Contrasting

Order By: Relevance

“…For comparison with Stevens & Cuthill [28], edge detection analysis was carried out using a Laplacian-of-Gaussian edge detector followed by the Hough transform as a straight line (and thus triangle outline) detector. Mortality was higher the greater the number of correct triangle sides detected by the Hough transform (odds ratio ¼ 1.22 (95% CI 1.00-1.48), x 2 ¼ 3.88, d.f.…”

Section: Results (A) Correlations Between Bird and Human Detection Pementioning

confidence: 99%

See 1 more Smart Citation

Background complexity and the detectability of camouflaged targets by birds and humans

Xiao¹,

Cuthill²

2016

Proc. R. Soc. B.

View full text Add to dashboard Cite

Remaining undetected is often key to survival, and camouflage is a widespread solution. However, extrinsic to the animal itself, the complexity of the background may be important. This has been shown in laboratory experiments using artificially patterned prey and backgrounds, but the mechanism remains obscure (not least because 'complexity' is a multifaceted concept). In this study, we determined the best predictors of detection by wild birds and human participants searching for the same cryptic targets on trees in the field. We compared detection success to metrics of background complexity and 'visual clutter' adapted from the human visual salience literature. For both birds and humans, the factor that explained most of the variation in detectability was the textural complexity of the tree bark as measured by a metric of feature congestion (specifically, many nearby edges in the background). For birds, this swamped any effects of colour match to the local surroundings, although for humans, local luminance disparities between the target and tree became important. For both taxa, a more abstract measure of complexity, entropy, was a poorer predictor. Our results point to the common features of background complexity that affect visual search in birds and humans, and how to quantify them.

show abstract

Section: Results (A) Correlations Between Bird and Human Detection Pementioning

confidence: 99%

“…This and other passerine species have been seen predating the artificial prey in previous experiments. The colour was quantified using spectrophotometry and avian colour space modelling (following [28]). …”

Section: Methodsmentioning

confidence: 99%

Background complexity and the detectability of camouflaged targets by birds and humans

Xiao¹,

Cuthill²

2016

Proc. R. Soc. B.

View full text Add to dashboard Cite

show abstract

“…This view was first promoted by Cott (1940). Predators have been shown to use edge properties of prey in detection (Cuthill et al 2005;Stevens and Cuthill 2006).…”

Section: D Background Matchingmentioning

confidence: 99%

Three-Dimensional Camouflage: Exploiting Photons to Conceal Form

Penacchio

Lovell

Cuthill³

et al. 2015

The American Naturalist

View full text Add to dashboard Cite

Many animals have a gradation of body color, termed "countershading," where the areas that are typically exposed to more light are darker. One hypothesis is that this patterning enhances visual camouflage by making the retinal image of the animal match that of the background, a fundamentally two-dimensional theory. More controversially, countershading may also obliterate cues to three-dimensional (3D) shape delivered by shading. Despite relying on distinct cognitive mechanisms, these two potential functions hitherto have been amalgamated in the literature. It has previously not been possible to validate either hypothesis empirically, because there has been no general theory of optimal countershading that allows quantitative predictions to be made about the many environmental parameters involved. Here we unpack the logical distinction between using countershading for background matching and using it to obliterate 3D shape. We use computational modeling to determine the optimal coloration for the camouflage of 3D shape. Our model of 3D concealment is derived from the physics of light and informed by perceptual psychology: we simulate a 3D world that incorporates naturalistic lighting environments. The model allows us to predict countershading coloration for terrestrial environments, for any body shape and a wide range of ecologically relevant parameters. The approach can be generalized to any light distribution, including those underwater.

show abstract

“…Even if most of the individual edge segments are visible, it might be possible to confuse the edge grouping processes by deleting some edge information, by distorting the location and polarity information about edges that are present, and by inserting misleading information about edges that are not actually present (Stevens & Cuthill 2006).…”

Section: Edge Detection Processes: Disruption and Camouflagementioning

confidence: 99%

Camouflage and visual perception

Trościanko

Benton

Lovell

et al. 2008

Phil. Trans. R. Soc. B

180

128

View full text Add to dashboard Cite

How does an animal conceal itself from visual detection by other animals? This review paper seeks to identify general principles that may apply in this broad area. It considers mechanisms of visual encoding, of grouping and object encoding, and of search. In most cases, the evidence base comes from studies of humans or species whose vision approximates to that of humans. The effort is hampered by a relatively sparse literature on visual function in natural environments and with complex foraging tasks. However, some general constraints emerge as being potentially powerful principles in understanding concealment-a 'constraint' here means a set of simplifying assumptions. Strategies that disrupt the unambiguous encoding of discontinuities of intensity (edges), and of other key visual attributes, such as motion, are key here. Similar strategies may also defeat grouping and object-encoding mechanisms. Finally, the paper considers how we may understand the processes of search for complex targets in complex scenes. The aim is to provide a number of pointers towards issues, which may be of assistance in understanding camouflage and concealment, particularly with reference to how visual systems can detect the shape of complex, concealed objects.

show abstract

Disruptive coloration, crypsis and edge detection in early visual processing

Cited by 219 publications

References 34 publications

Background complexity and the detectability of camouflaged targets by birds and humans

Background complexity and the detectability of camouflaged targets by birds and humans

Three-Dimensional Camouflage: Exploiting Photons to Conceal Form

Camouflage and visual perception

Contact Info

Product

Resources

About