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Feedback and Surround Modulated Boundary Detection

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Abstract

Edges are key components of any visual scene to the extent that we can recognise objects merely by their silhouettes. The human visual system captures edge information through neurons in the visual cortex that are sensitive to both intensity discontinuities and particular orientations. The “classical approach” assumes that these cells are only responsive to the stimulus present within their receptive fields, however, recent studies demonstrate that surrounding regions and inter-areal feedback connections influence their responses significantly. In this work we propose a biologically-inspired edge detection model in which orientation selective neurons are represented through the first derivative of a Gaussian function resembling double-opponent cells in the primary visual cortex (V1). In our model we account for four kinds of receptive field surround, i.e. full, far, iso- and orthogonal-orientation, whose contributions are contrast-dependant. The output signal from V1 is pooled in its perpendicular direction by larger V2 neurons employing a contrast-variant centre-surround kernel. We further introduce a feedback connection from higher-level visual areas to the lower ones. The results of our model on three benchmark datasets show a big improvement compared to the current non-learning and biologically-inspired state-of-the-art algorithms while being competitive to the learning-based methods.

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Notes

  1. The source code and all the experimental materials are available at https://github.com/ArashAkbarinia/BoundaryDetection.

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Acknowledgements

We would like to thank Dr. Xavier Otazu, members of the NeuroBiT Group at the Centre de Visió per Computador, Dr. Thorsten Hansen, and anonymous reviewers of the manuscript for their thoughtful insights and comments.

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Authors and Affiliations

  1. Centre de Visió per Computador, Universitat Autònoma de Barcelona, Barcelona, Spain

    Arash Akbarinia & C. Alejandro Parraga

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  1. Arash Akbarinia
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  2. C. Alejandro Parraga
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Correspondence to Arash Akbarinia.

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Communicated by Edwin Hancock, Richard Wilson, Will Smith, Adrian Bors and Nick Pears.

This work was funded by the Spanish Secretary of Research and Innovation (TIN2013-41751-P and TIN2013-49982-EXP) and the CERCA Programme from the Generalitat de Catalunya.

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Akbarinia, A., Parraga, C.A. Feedback and Surround Modulated Boundary Detection. Int J Comput Vis 126, 1367–1380 (2018). https://doi.org/10.1007/s11263-017-1035-5

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