Conference poster

G. Azzopardi and N. Petkov, “A computational model of push-pull inhibition of simple cells with application to contour detection”, ECVP, Belgrade, Serbia, 2014
[abstract] [poster]

Abstract

We propose a computational model of push-pull inhibition (ON inhibition in OFF subfields and vice-versa) of simple cells. It is based on an existing orientation-selective model called Combination of Receptive Fields (CORF), which combines, by an AND-type operation, the responses of model LGN cells with appropriately aligned center-surround receptive fields. A push-pull response is computed as the response of a CORF model cell that is selective for a stimulus with preferred orientation and contrast minus a fraction of the response of a CORF model that responds to the same stimulus but of opposite contrast. The proposed push-pull model exhibits an improved signal-to-noise ratio and achieves two properties that are observed in real simple cells: contrast-dependent changes in spatial frequency tuning and separability of spatial frequency and orientation. For two benchmark data sets (RuG: 40 images, Berkeley: 500 images), we demonstrated that the proposed push-pull model outperforms (with very high statistical significance) the Gabor function model with (and without) surround suppression and Canny contour detector. The push-pull model that we propose contributes to a better understanding of how the brain processes visual information and is highly effective in edge detection, which is considered as the primary biological role of simple cells.

Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, the Netherlands