One of the first instances of using a computational model to research visual perception was in response to the classic problem “how does the visual system ‘know’ that the varied appearance of a coloured surface is a property of the surface rather than its illumination?” (Gordon, 2004, p. 187). Both Land and McCann (1971) and Horn (1974) suggested that the key distinction is that the effect of a change in illumination is gradual, whereas changes that are because of an object’s edges are abrupt. To investigate, they recorded output differences from two adjacent detectors which sample lightness values. They found that the difference in output on a uniform surface with a change in illumination was small and insignificant, whereas when the detectors were on either side of a boundary between two surfaces of different lightness, there was a large difference in output. This suggests that our visual system uses a similar method to detect important changes in surfaces properties and distinguish them from transitory changes in illumin...
... middle of paper ...
...em such as vision, it is important not to oversimplify the idea to the point where a model is no longer representative of how the brain is working.
Dreyfus, H. L. (1972). What computers can’t do: A critique of artificial reason. New York: Harper & Row.
Gordon, I. E. (2004). Theories of visual perception (3rd ed.). Hove: Psychology Press.
Horn, B. K. (1974). Determining lightness from an image. Computer Graphics and Image Processing. 3, 277-299.
Land, E. H. & McCann, J. J. (1971). Lightness and retinex theory. Journal of the Optical Society of America, 61, 1-11.
Marr, D. (1982). Vision: A computational investigation into the human representation and processing of visual information. San Francisco, CA: W. H. Freeman.
Marr, D. & Hildreth, E. (1980) Theory of edge detection. Proceedings of the Royal Society of London, Series B, 207, 187-217.
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