• DocumentCode
    1727191
  • Title

    The algorithms of natural vision: the multi-channel gradient model

  • Author

    McOwan, P.W. ; Johnston, A.

  • Author_Institution
    Univ. Coll. London, UK
  • fYear
    1995
  • Firstpage
    319
  • Lastpage
    324
  • Abstract
    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
  • Keywords
    brain models; computer vision; neurophysiology; parallel architectures; physiological models; psychology; visual perception; artificial vision systems; biological algorithm deciphering; brain; cortical tissue; environmentally robust techniques; evolution; human visual perception; multi-channel gradient model; natural vision; neurophysiological evidence; parallel architecture; primate visual perception; psychophysical evidence; visual information processing strategies; visual signal interpretation;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Genetic Algorithms in Engineering Systems: Innovations and Applications, 1995. GALESIA. First International Conference on (Conf. Publ. No. 414)
  • Conference_Location
    Sheffield
  • Print_ISBN
    0-85296-650-4
  • Type

    conf

  • DOI
    10.1049/cp:19951069
  • Filename
    501692