DocumentCode :
1901879
Title :
A cortical structure for real world image processing
Author :
Kopecz, Jörg
Author_Institution :
Inst. fuer Neuroinf., Ruhr-Univ., Bochum, Germany
fYear :
1993
fDate :
1993
Firstpage :
138
Abstract :
Neural architecture as found in the mammalian visual cortex is used for visual processing of real world camera images. The neural architecture used does not refer to classical neural nets but to more global characteristics such as the typical receptive field characteristics, two-dimensional cortical structure, local operations and topographic arrangement of cells. The self-organization algorithm analyzed and named elastic field algorithm is an alternative to the Kohonen model. Known facts from image processing are included in the model to achieve high performance
Keywords :
computer vision; self-organising feature maps; stereo image processing; cortical structure; elastic field algorithm; global characteristics; local operations; neural architecture; real world camera images; real world image processing; receptive field characteristics; topographic arrangement; two-dimensional cortical structure; visual processing; Biology computing; Cameras; Electronic mail; Gabor filters; Histograms; Image coding; Image processing; Image segmentation; Robot vision systems; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1993., IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0999-5
Type :
conf
DOI :
10.1109/ICNN.1993.298517
Filename :
298517
Link To Document :
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