The algorithms of natural vision: the multi-channel gradient model
The algorithms of natural vision: the multi-channel gradient model
- Author(s): P.W. McOwan and A. Johnston
- DOI: 10.1049/cp:19951069
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- Author(s): P.W. McOwan and A. Johnston Source: 1st International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications (GALESIA), 1995 p. 319 – 324
- Conference: 1st International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications (GALESIA)
Nature, through the process of evolution, has developed strategies for the processing of visual information. These algorithms have been optimised over eons to maximise the organism's ability to survive in the real world. Hence, the techniques employed are efficient, environmentally robust and practical for implementation in the parallel architecture of the brain. Primate and human visual perception are the most developed, with a high percentage of cortical tissue devoted to interpreting the visual signal. Thus, we may examine the extensive neurophysiological and psychophysical evidence available in an attempt to decipher the algorithms used by biology in an effort to build artificial vision systems which incorporate many of the desirable traits of natural vision.
Inspec keywords: physiological models; parallel architectures; visual perception; neurophysiology; brain models; psychology; computer vision
Subjects: General, theoretical, and mathematical biophysics; Pattern recognition; Psychophysics of vision, visual perception, binocular vision; Biophysics of neurophysiological processes; Systems theory applications in biology and medicine
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