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
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