DocumentCode
847209
Title
Cepstral filtering on a columnar image architecture: a fast algorithm for binocular stereo segmentation
Author
Yeshurun, Yehezkel ; Schwartz, Eric L.
Author_Institution
Dept. of Psychiatry, New York Univ. Med. Center, NY, USA
Volume
11
Issue
7
fYear
1989
fDate
7/1/1989 12:00:00 AM
Firstpage
759
Lastpage
767
Abstract
Many primate visual cortex architectures have a prominent feature responsible for the mixing of left and right eye visual data: ocular dominance columns represent thin (about 5-10 minutes of arc) strips of alternating left and right eye input to the brain. It is shown that such an architecture, when operated upon with a cepstral filter, provides a strong cue for binocular stereopsis. Specifically, the vector of binocular disparity may be easily identified in the output of the (columnar based) cepstral filter. This algorithm is illustrated with application to a random dot stereogram and to natural images. The authors suggest that this provides a fast algorithm for stereo segmentation, in a machine vision context. In a biological context, it may provide a computational rationale for the existence of columnar systems with regard to both ocular mixing and other visual modalities that have a columnar architecture
Keywords
computer vision; filtering and prediction theory; pattern recognition; visual perception; binocular disparity; binocular stereo segmentation; binocular stereopsis; brain; cepstral filter; columnar image architecture; computer vision; machine vision; natural images; ocular dominance columns; pattern recognition; primate visual cortex architectures; random dot stereogram; stereo segmentation; Biomedical imaging; Cepstral analysis; Filtering algorithms; Filters; Humans; Image segmentation; Laboratories; Layout; Machine vision; Psychiatry;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.192471
Filename
192471
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