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
Link To Document :
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