Contour detection based on a non-classical receptive field model with butterfly-shaped inhibition subregions

Authors:
Chi Zeng;Yongjie Li;Kaifu Yang;Chaoyi Li
Affiliations:
Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Section 2, No. 4, North Jianshe Road, ...;Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Section 2, No. 4, North Jianshe Road, ...;Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Section 2, No. 4, North Jianshe Road, ...;Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Section 2, No. 4, North Jianshe Road, ...
Venue:
Neurocomputing
Year:
2011

Citing 5
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Contour detection based on nonclassical receptive field inhibition

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Contour detection model with multi-scale integration based on non-classical receptive field

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Abstract

Physiological studies show that the response of classical receptive field (CRF) to visual stimulus could be suppressed by non-classical receptive field (NCRF) inhibition of the neurons in primary visual cortex (V1) and most of CRFs and NCRFs in V1 are orientation-selective. In addition, surround inhibition is normally spatially asymmetric. Inspired by these visual mechanisms, we proposed a feasible contour detection method based on an improved orientation-selective inhibition model in this paper. A butterfly-formed surrounding area is employed for the computation of inhibition term, and only one side subregion that produces less inhibition contributes to cell's response, which could provide a flexible inhibitory effect for the NCRF modulation on CRF. Comparisons with other visual contour detection models show that the proposed model can suppress texture effectively while retaining contours as much as possible.