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  Visual Segmentation without Classification in a Model of the Primary Visual Cortex

Li, Z.(1997). Visual Segmentation without Classification in a Model of the Primary Visual Cortex (AIM-1613). Cambridge, MA, USA: Massachusetts Institute of Technology (MIT).

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Item Permalink: https://hdl.handle.net/21.11116/0000-0002-DDCE-E Version Permalink: https://hdl.handle.net/21.11116/0000-0002-DDD3-7
Genre: Report

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https://dspace.mit.edu/handle/1721.1/7247 (Publisher version)
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 Creators:
Li, Z1, Author           
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1External Organizations, ou_persistent22              

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 Abstract: Stimuli outside classical receptive fields significantly influence the neurons' activities in primary visual cortex. We propose that such contextual influences are used to segment regions by detecting the breakdown of homogeneity or translation invariance in the input, thus computing global region boundaries using local interactions. This is implemented in a biologically based model of V1, and demonstrated in examples of texture segmentation and figure-ground segregation. By contrast with traditional approaches, segmentation occurs without classification or comparison of features within or between regions and is performed by exactly the same neural circuit responsible for the dual problem of the grouping and enhancement of contours.

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 Dates: 1997-08
 Publication Status: Issued
 Pages: 8
 Publishing info: Cambridge, MA, USA : Massachusetts Institute of Technology (MIT)
 Table of Contents: -
 Rev. Type: -
 Identifiers: Report Nr.: AIM-1613
Report Nr.: CBCL-153
 Degree: -

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